Undermind Research Topic: I want to find research articles about how search query time for an online search system (like Google or Google scholar, for example) affects user experience and usage. I want empirical studies that measure changes in user behavior.

Research topic

I want to find research articles about how search query time for an online search system (like Google or Google scholar, for example) affects user experience and usage. I want empirical studies that measure changes in user behavior.

Report

Precisely Relevant Studies on Query Time

Studies that empirically investigate the impact of search query time on user behavior in online search systems, specifically measuring changes in metrics like click behavior and engagement.
References: [1, 2, 4, 5, 6, 8]
Details:
- [1, 2, 4] Conduct controlled user studies examining user sensitivity to response latency and analyze Yahoo search query logs to reveal behavioral changes.
- [5] Investigates query response delays using Information Foraging Theory, highlighting interaction changes due to delays.
- [6] Analyzes physiological and emotional responses to latency, emphasizing changes in click behavior.
- [8] Explores differences in user behavior and tolerance in mobile searches compared to desktop.

Studies on User Preferences and Tolerance Thresholds

Focus on understanding user tolerance to different levels of latency and the impact on preferences for search systems.
References: [3, 7, 13]
Details:
- [3] Compares user preferences between fast and slow search engines, identifying specific latency thresholds affecting choice.
- [7, 13] Investigate willingness to wait within "slow search" systems, examining behavior modification over time for quality trade-offs.

Examining Cognitive, Emotional, and Physiological Responses

Studies that explore the cognitive load and psychological effects of delayed search query times.
References: [6, 8, 10]
Details:
- [6] Uses physiological experiments to show attentional shifts and emotional effects due to latency.
- [8] Looks at mobile-specific emotional responses, reporting user frustration at higher latency durations.
- [10] Studies emotional reactions under time constraints and system delays, measuring impact on satisfaction and task difficulty.

Theoretical Model Applications and Hypotheses

Research applying theoretical frameworks like Information Foraging and Search Economic Theories to explain user behavior under response latency.
References: [5, 9]
Details:
- [5] Employs theories to hypothesize and test behaviors under delays, noting differences from expected theoretical predictions.
- [9] Explores decision-making impacts under delays, outlining theories about user effort minimization during search.

Large-Scale Data and Log Analysis

Studies leveraging query logs to understand real-world user behavior in response to latency.
References: [1, 2, 6]
Details:
- [1, 2] Analyze Yahoo Web Search logs, correlating latency increases with changes in click behavior and search engagement.
- [6] Conducts a large-scale analysis of click behavior changes using web query logs from a major search engine.

Timeline and Development of Ideas

Early Foundations (2000-2008):
- Initial studies, such as by Hoxmeier and Dicesare (2000) [16], begin exploring the impact of system response time on user satisfaction, noting dissatisfaction with increased response time. This set the stage for identifying thresholds of acceptability.
- Brutlag et al. (2008) [3] expand by empirically comparing user preferences for fast vs. slow search engine latencies, establishing more concrete insights into user sensitivity and behavior changes, such as abandonment of slower systems.
Advancing Methodologies and Theories (2014-2017):
- Arapakis et al. (2014) [2] and Bai et al. (2017) [1] contribute significantly through controlled user studies and log analyses, illustrating the thresholds of latency that affect user satisfaction and click behavior.
- Maxwell and Azzopardi (2014) [5] introduce Information Foraging and Search Economic Theories to examine search behavior under latency, providing deeper theoretical frameworks.
Exploring Cognitive and Emotional Effects (2015-2016):
- Barreda-Ángeles et al. (2015) [6] delve into physiological and emotional responses to latency, uncovering nuanced attentional and emotional shifts even with minor delays.
- Research in 2016 [10][15] extends to assessing time constraints and delays, diversifying focus to cognitive and task performance impacts under structured conditions.
Nuanced Contextual Analyses (2016-2021):
- Studies like Burton and Collins-Thompson (2016) [7] and Arapakis et al. (2021) [8] refine understanding by focusing on user adaptability in slow search scenarios and mobile vs. desktop latency tolerances, highlighting situational variances in user behavior.

Key Contributors and Clusters

Ioannis Arapakis and Collaborators:
- A significant cluster of research led by Arapakis, with contributions to understanding both theoretical and applied aspects of response latency on user behavior in search systems through various studies [2][4][8].
David Maxwell and Leif Azzopardi:
- This team provided foundational theoretical contributions using Information Foraging Theory and Search Economic Theory to elucidate user behavior dynamics under latency influence [5][15].

These researchers and their collaborative works have consistently advanced domain knowledge by integrating empirical findings with theoretical models, shaping current understanding and prompting further inquiry into adaptive search systems and behavior insights.

Bokeh Application

References

Last 5 years

Last 2 years

> 1 citation per year

> 5 citations per year

Topic Match

Cit./Year

Year

Paper

Paper Relevance Summary

99.8%

2.3

2017

[1] Understanding and Leveraging the Impact of Response Latency on User Behaviour in Web Search Xiao Bai, ..., and Ana Freire ACM Transactions on Information Systems (TOIS) 2017 - 16 citations - Show abstract - Cite - PDF 99.8% topic match

Provides empirical evidence on the impact of response latency on user behavior. Controlled user study and large-scale analysis show increased sensitivity and changed click behavior with delayed response times. Focuses on web search systems, specifically Yahoo Web Search; highlights latency thresholds affecting user experience.

Provides empirical evidence on the impact of response latency on user behavior. Controlled user study and large-scale analysis show increased sensitivity and changed click behavior with delayed response times. Focuses on web search systems, specifically Yahoo Web Search; highlights latency thresholds affecting user experience.

99.8%

13.0

2014

[2] Impact of response latency on user behavior in web search Ioannis Arapakis, ..., and B. B. Cambazoglu Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval 2014 - 132 citations - Show abstract - Cite 99.8% topic match

Provides empirical investigation on the impact of response latency on user behavior. Includes a controlled study and an analysis of Yahoo query logs. Demonstrates that higher latency decreases click-through rates, highlighting the sensitivity of users to delays.

Provides empirical investigation on the impact of response latency on user behavior. Includes a controlled study and an analysis of Yahoo query logs. Demonstrates that higher latency decreases click-through rates, highlighting the sensitivity of users to delays.

99.8%

3.0

2008

[3] User Preference and Search Engine Latency J. Brutlag, ..., and M. Stone Journal Not Provided 2008 - 50 citations - Show abstract - Cite 99.8% topic match

Provides empirical comparison of search engine latency impacts on user preferences. Evaluates user choices between search engines with fixed fast latency (250 ms) and various slow latencies (2-5s). Demonstrates increased user preference for faster search engines as latency exceeds 3 seconds, relevant for understanding behavior changes due to query time.

Provides empirical comparison of search engine latency impacts on user preferences. Evaluates user choices between search engines with fixed fast latency (250 ms) and various slow latencies (2-5s). Demonstrates increased user preference for faster search engines as latency exceeds 3 seconds, relevant for understanding behavior changes due to query time.

99.7%

0.0

2014

[4] A Controlled User Study on Human Perception of Web Search Latency ∗ Ioannis Arapakis and Xiao Bai Journal Not Provided 2014 - 0 citations - Show abstract - Cite 99.7% topic match

Shows how response latency affects user behavior in web search. Examines user sensitivity to latency and impacts on engagement and satisfaction. Includes controlled studies on user perception and bias due to search site branding.

Shows how response latency affects user behavior in web search. Examines user sensitivity to latency and impacts on engagement and satisfaction. Includes controlled studies on user perception and bias due to search site branding.

99.7%

3.0

2014

[5] Stuck in traffic: how temporal delays affect search behaviour David Maxwell and L. Azzopardi Proceedings of the 5th Information Interaction in Context Symposium 2014 - 30 citations - Show abstract - Cite - PDF 99.7% topic match

Investigates query response delays and user search behavior. Examines user interactions through a laboratory study, focusing on query response and document download delays. Provides empirical data on how delays influence the number of queries, documents examined, and search depth, relevant to evaluating user behavior changes.

Investigates query response delays and user search behavior. Examines user interactions through a laboratory study, focusing on query response and document download delays. Provides empirical data on how delays influence the number of queries, documents examined, and search depth, relevant to evaluating user behavior changes.

99.5%

3.0

2015

[6] Unconscious Physiological Effects of Search Latency on Users and Their Click Behaviour Miguel Barreda-Ángeles, ..., and Alexandre Pereda-Baños Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval 2015 - 27 citations - Show abstract - Cite 99.5% topic match

Provides empirical insights on search latency impacts on user behavior. Conducts a controlled experiment revealing physiological and emotional effects of response latency. Analyzes Yahoo query logs to show significant changes in click behavior with varying response times.

Provides empirical insights on search latency impacts on user behavior. Conducts a controlled experiment revealing physiological and emotional effects of response latency. Analyzes Yahoo query logs to show significant changes in click behavior with varying response times.

98.0%

0.9

2016

[7] User Behavior in Asynchronous Slow Search Ryan Burton and Kevyn Collins-Thompson Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval 2016 - 7 citations - Show abstract - Cite 98.0% topic match

Provides empirical insights on user behavior with asynchronous slow search. Analyzes users' willingness to trade query speed for improved result quality in a Web search system. Investigates how search outcomes and user time allocation change with asynchronous slow search, relevant to examining response times.

Provides empirical insights on user behavior with asynchronous slow search. Analyzes users' willingness to trade query speed for improved result quality in a Web search system. Investigates how search outcomes and user time allocation change with asynchronous slow search, relevant to examining response times.

90.8%

2.5

2021

[8] Impact of Response Latency on User Behaviour in Mobile Web Search Ioannis Arapakis, ..., and M. Pielot Proceedings of the 2021 Conference on Human Information Interaction and Retrieval 2021 - 9 citations - Show abstract - Cite - PDF 90.8% topic match

Provides insights into response latency effects on mobile web search behavior. Conducted a controlled study showing users tolerate up to 7-10 seconds delay before significant negative impact. Focuses on mobile context rather than general online search systems like Google; lacks detailed empirical metrics on user behavior changes.

Provides insights into response latency effects on mobile web search behavior. Conducted a controlled study showing users tolerate up to 7-10 seconds delay before significant negative impact. Focuses on mobile context rather than general online search systems like Google; lacks detailed empirical metrics on user behavior changes.

86.4%

0.0

2006

[9] Information Search on the Web: Understanding the Impact of Response Time Delays with Information Foraging Theory Nolan J. Taylor and A. Dennis Social Science Research Network 2006 - 0 citations - Show abstract - Cite 86.4% topic match

Shows how response time delays impact web information search behavior. Delays lead to decreased search efforts and quality by users. Focuses on web environments; likely includes empirical data relevant to user experience in search systems.

Shows how response time delays impact web information search behavior. Delays lead to decreased search efforts and quality by users. Focuses on web environments; likely includes empirical data relevant to user experience in search systems.

68.2%

4.9

2016

[10] Impacts of Time Constraints and System Delays on User Experience Anita Crescenzi, ..., and L. Azzopardi Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval 2016 - 42 citations - Show abstract - Cite 68.2% topic match

Investigates the impact of time constraints and system delays on user experience. Study with 45 participants examined effects of 5-minute time limits and 5-second query delays. Reports increased task difficulty, lower satisfaction, and more metacognitive monitoring under delays, but does not isolate query time effects on search systems exclusively.

Investigates the impact of time constraints and system delays on user experience. Study with 45 participants examined effects of 5-minute time limits and 5-second query delays. Reports increased task difficulty, lower satisfaction, and more metacognitive monitoring under delays, but does not isolate query time effects on search systems exclusively.

64.5%

0.0

2021

[11] Effects of Time Constraints and Search Results Presentation on Web Search M. Beijen Journal Not Provided 2021 - 0 citations - Show abstract - Cite Abstract: Everybody experiences time constraints in their daytoday lives. These time constraints may induce stress, possibly influencing our judgment abilities and behavior. In contemporary daily life, search en gines are regularly consulted to look for information online with searchers commonly experiencing time constraints in the web search process. With an increasing percentage of the global population having access to the internet and thus a search engine, more people will experience being timeconstrained during the search process. The generally unfavorable consequences of these time constraints have been examined in vari ous stages of the search process. Despite the importance of this issue, how the design of the web page showing the search results, or the Search Engine Results Page (SERP), may benefit in time constrained web searches constitutes a substantial and important knowledge gap that this work aims to address. Concretely, we investigate how different time constraints influence task performance and search behavior. Consequently, we aim to determine to what extent various SERP interfaces are sus ceptible to the effects of time constraints. We also want to know how different SERP interfaces impact user experience and we examine to what extent affinity for technology interaction moderates the rela tionship between time constraint and task performance. We aim to address these questions through a crowdsourced 4 (SERP interfaces) × 4 (time con straints) betweensubjects factorial design user study in which participants are tasked with searching the web to find a list of arguments supporting or opposing a controversial topic. To examine to what extent user interfaces are susceptible to the effects of time constraints, participants make use of a mock search system displaying one of four SERP interfaces depending on the experimental condition: a list interface (baseline, traditional interface), a grid interface, a listlike interface without the snippet, and an interface with the snippet placed to the right of other data. The used time constraints are 2, 5, and 8 minutes in addition to a condition without a time constraint. The effects of SERP interfaces and time constraints are evaluated in terms of task performance metrics, search behavior, and user experience. Results have shown that task performance is considerably decreased by stricter time constraints. Also, as time constraints tightened, the rate at which participants issued queries increased. Exploratory results suggest this comes as the cost of reduced depth to which individuals click on results in the ranked list. As for the interaction between SERP interfaces and time constraints, SERP interfaces have not been found to be susceptible to the effects of time constraints. Interestingly, user experience was neither worsened nor improved because of the experimental SERP interfaces and affinity for technology interaction was not found to play a moderating role in the relationship between time constraints and task performance. 64.5% topic match

Examines the impact of time constraints on web search behavior. Shows that stricter time constraints increase query rate but decrease click depth. Does not specifically isolate search query response time, but relevant to user behavior under time pressure.

Examines the impact of time constraints on web search behavior. Shows that stricter time constraints increase query rate but decrease click depth. Does not specifically isolate search query response time, but relevant to user behavior under time pressure.

56.8%

1.4

2022

[12] A Reference Dependence Approach to Enhancing Early Prediction of Session Behavior and Satisfaction T. Brown and Jiqun Liu 2022 ACM/IEEE Joint Conference on Digital Libraries (JCDL) 2022 - 3 citations - Show abstract - Cite 56.8% topic match

Shows user satisfaction decay based on search time expectations. Demonstrates rapid user satisfaction decay logarithmically after surpassing a one-minute search time. Relevant if focus includes expectation-driven behavior and its impact on satisfaction decay in search systems.

Shows user satisfaction decay based on search time expectations. Demonstrates rapid user satisfaction decay logarithmically after surpassing a one-minute search time. Relevant if focus includes expectation-driven behavior and its impact on satisfaction decay in search systems.

54.2%

0.0

2016

[13] Understanding User Adjustment to Slow Search Ryan Burton and Kevyn Collins-Thompson Journal Not Provided 2016 - 0 citations - Show abstract - Cite 54.2% topic match

Provides an analysis of user behavior with slow search systems. Shows that user behavior adjusts based on retrieval speed and perceived relevance gains. Focuses on slow search's robustness; may indirectly relate to query response time effects on user experience.

Provides an analysis of user behavior with slow search systems. Shows that user behavior adjusts based on retrieval speed and perceived relevance gains. Focuses on slow search's robustness; may indirectly relate to query response time effects on user experience.

45.9%

2.5

2009

[14] Evaluating web search using task completion time Ya Xu and David Mease Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval 2009 - 38 citations - Show abstract - Cite 45.9% topic match

Shows the negative impact of total search time on user satisfaction. Analyzes data to verify the inverse relationship between search time and user satisfaction for specific tasks. Focuses on web search algorithms and task completion time, not directly on query response time.

Shows the negative impact of total search time on user satisfaction. Analyzes data to verify the inverse relationship between search time and user satisfaction for specific tasks. Focuses on web search algorithms and task completion time, not directly on query response time.

39.7%

3.7

2015

[15] Time Pressure and System Delays in Information Search Anita Crescenzi, ..., and L. Azzopardi Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval 2015 - 34 citations - Show abstract - Cite - PDF 39.7% topic match

Shows the impact of system delays and time pressure on search behavior. Indicates that time pressure leads to higher query rates and reduced document interaction. Finds minimal significant impact from system delays alone, focusing more on time pressure.

Shows the impact of system delays and time pressure on search behavior. Indicates that time pressure leads to higher query rates and reduced document interaction. Finds minimal significant impact from system delays alone, focusing more on time pressure.

27.8%

8.6

2000

[16] System Response Time and User Satisfaction: An Experimental Study of Browser-based Applications John A. Hoxmeier and Christopher A. Dicesare Journal Not Provided 2000 - 212 citations - Show abstract - Cite Abstract: With rapid advances in hardware speed and data communication bandwidth, one might not expect to have to deal with issues such as response time and system performance. But these issues remain a very real concern today. Lengthy system response times may cause lower satisfaction and poor productivity among users. Lowered user satisfaction may lead to discontinued use of an application, especially in discretionary applications such as those found on the Internet. The intent of this experimental research is to (1) substantiate that slow system response time leads to dissatisfaction; (2) assess the point at which users may become dissatisfied with system response time; (3) determine a threshold at which dissatisfaction may lead to discontinued use of the application, and (4) determine if experience influences response time tolerance. The results showed that indeed satisfaction does decrease as response time increases. However, instant response was not perceived as making the system easier to use or learn. It also showed that for discretionary applications, there appears to be a level of intolerance in the 12-second response range. Background and Introduction With rapid advances in hardware speed and data communication bandwidth, one might not expect to have to deal with issues such as response time and system performance. But these issues remain a very real concern today. As systems become more powerful, their applications become more complex as users expect more functionality and richer information. While response time is recognized as a component in some application usability and human factors studies (Goodwin, 1987; Nielsen, 1994; Shneiderman, 1991; Shneiderman, 1998) users today face similar system response time issues that faced users a decade ago. As web developers experience slow response times due to lengthy downloads of graphic intensive material, they are redesigning the sites to minimize this overhead. This will not be an acceptable long-term solution to accommodating electronic commerce. The network may have pockets of high-speed access and adequate bandwidth, but overall high-speed access is unavailable and many of the sites may not have been designed to handle the traffic and data volume 27.8% topic match

Investigates the impact of system response time on user satisfaction. Demonstrates that user satisfaction decreases as response time increases, with a critical threshold around 12 seconds. The study focuses on browser-based applications generally, not specifically on online search systems; empirical but broader context.

Investigates the impact of system response time on user satisfaction. Demonstrates that user satisfaction decreases as response time increases, with a critical threshold around 12 seconds. The study focuses on browser-based applications generally, not specifically on online search systems; empirical but broader context.

26.9%

12.4

2018

[17] Measuring the Utility of Search Engine Result Pages: An Information Foraging Based Measure L. Azzopardi, ..., and Nick Craswell The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval 2018 - 77 citations - Show abstract - Cite - PDF 26.9% topic match

Provides a measure for evaluating user behavior and utility in search engine result pages. Analyzes 1000 popular queries and compares foraging based measure against common measures, focusing on user behavior metrics like stopping rank and time spent. Does not specifically measure the impact of query response time on user experience; focuses more broadly on search utility and behavior.

Provides a measure for evaluating user behavior and utility in search engine result pages. Analyzes 1000 popular queries and compares foraging based measure against common measures, focusing on user behavior metrics like stopping rank and time spent. Does not specifically measure the impact of query response time on user experience; focuses more broadly on search utility and behavior.

25.1%

1.2

2017

[18] Investigating Users' Time Perception during Web Search Cheng Luo, ..., and Shaoping Ma Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval 2017 - 9 citations - Show abstract - Cite 25.1% topic match

Examines users' time perception in web search contexts. Explores the difference between perceived and objective time during web search sessions, showing psychological effects like Vierordt's law. Relevance may be limited as it focuses on time perception rather than direct, empirical measurements of query response time on user behavior.

Examines users' time perception in web search contexts. Explores the difference between perceived and objective time during web search sessions, showing psychological effects like Vierordt's law. Relevance may be limited as it focuses on time perception rather than direct, empirical measurements of query response time on user behavior.

19.9%

2.0

2013

[19] Understanding how people interact with web search results that change in real-time using implicit feedback Jin Young Kim, ..., and Dmitry Lagun Proceedings of the 22nd ACM international conference on Information & Knowledge Management 2013 - 22 citations - Show abstract - Cite 19.9% topic match

Provides insights into user engagement with real-time dynamic search results. Compares traditional vs. dynamically re-ranked interfaces using implicit feedback to study user behavior and engagement. Focuses on interface changes rather than measuring query response time impact on user behavior.

Provides insights into user engagement with real-time dynamic search results. Compares traditional vs. dynamically re-ranked interfaces using implicit feedback to study user behavior and engagement. Focuses on interface changes rather than measuring query response time impact on user behavior.

17.7%

8.5

2013

[20] A provider-side view of web search response time Yingying Chen, ..., and Zhi-Li Zhang Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM 2013 - 94 citations - Show abstract - Cite - PDF 17.7% topic match

Develops an analysis framework for understanding SRT in web search services. Shows SRT variations due to factors like network characteristics and query nature. Focuses on diagnosing performance anomalies rather than measuring user behavior changes.

Develops an analysis framework for understanding SRT in web search services. Shows SRT variations due to factors like network characteristics and query nature. Focuses on diagnosing performance anomalies rather than measuring user behavior changes.

17.0%

0.0

2020

[21] Managing tail latency in large scale information retrieval systems J. Mackenzie ACM SIGIR Forum 2020 - 0 citations - Show abstract - Cite Abstract: As both the availability of internet access and the prominence of smart devices continue to increase, data is being generated at a rate faster than ever before. This massive increase in data production comes with many challenges, including efficiency concerns for the storage and retrieval of such large-scale data. However, users have grown to expect the sub-second response times that are common in most modern search engines, creating a problem --- how can such large amounts of data continue to be served efficiently enough to satisfy end users? This dissertation investigates several issues regarding tail latency in large-scale information retrieval systems. Tail latency corresponds to the high percentile latency that is observed from a system --- in the case of search, this latency typically corresponds to how long it takes for a query to be processed. In particular, keeping tail latency as low as possible translates to a good experience for all users, as tail latency is directly related to the worst-case latency and hence, the worst possible user experience. The key idea in targeting tail latency is to move from questions such as "what is the median latency of our search engine?" to questions which more accurately capture user experience such as "how many queries take more than 200ms to return answers?" or "what is the worst case latency that a user may be subject to, and how often might it occur?" While various strategies exist for efficiently processing queries over large textual corpora, prior research has focused almost entirely on improvements to the average processing time or cost of search systems. As a first contribution, we examine some state-of-the-art retrieval algorithms for two popular index organizations, and discuss the trade-offs between them, paying special attention to the notion of tail latency. This research uncovers a number of observations that are subsequently leveraged for improved search efficiency and effectiveness. We then propose and solve a new problem, which involves processing a number of related query variations together, known as multi-queries, to yield higher quality search results. We experiment with a number of algorithmic approaches to efficiently process these multi-queries, and report on the cost, efficiency, and effectiveness trade-offs present with each. Finally, we examine how predictive models can be used to improve the tail latency and end-to-end cost of a commonly used multi-stage retrieval architecture without impacting result effectiveness. By combining ideas from numerous areas of information retrieval, we propose a prediction framework which can be used for training and evaluating several efficiency/effectiveness trade-off parameters, resulting in improved trade-offs between cost, result quality, and tail latency. 17.0% topic match

Discusses tail latency in information retrieval systems. Examines trade-offs in retrieval algorithms and their impact on worst-case latency. Focuses on system efficiency and effectiveness rather than on direct user behavior changes.

Discusses tail latency in information retrieval systems. Examines trade-offs in retrieval algorithms and their impact on worst-case latency. Focuses on system efficiency and effectiveness rather than on direct user behavior changes.

16.7%

0.8

2016

[22] Manipulating Time Perception of Web Search Users Cheng Luo, ..., and Deli Yang Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval 2016 - 7 citations - Show abstract - Cite 16.7% topic match

Investigates the manipulation of time perception in web search users. Conducts a study with 50 participants, showing higher perceived time duration in high temporal relevance environments. Focuses on subjective time perception rather than direct empirical measures of query response time on behavior.

Investigates the manipulation of time perception in web search users. Conducts a study with 50 participants, showing higher perceived time duration in high temporal relevance environments. Focuses on subjective time perception rather than direct empirical measures of query response time on behavior.

15.7%

30.5

2004

[23] A study on tolerable waiting time: how long are Web users willing to wait? F. Nah Behaviour & Information Technology 2004 - 620 citations - Show abstract - Cite - PDF 15.7% topic match

Provides tolerable waiting times for Web users. Assesses how feedback affects users' wait before abandoning a Web page. Focuses on general Web page download times, not specific to search query response time or behavior changes in search systems.

Provides tolerable waiting times for Web users. Assesses how feedback affects users' wait before abandoning a Web page. Focuses on general Web page download times, not specific to search query response time or behavior changes in search systems.

15.2%

7.1

2013

[24] Slow Search: Information Retrieval without Time Constraints J. Teevan, ..., and Yubin Kim Symposium on Human-Computer Interaction and Information Retrieval 2013 - 78 citations - Show abstract - Cite 15.2% topic match

Explores the concept of 'slow search' where speed requirements are relaxed. Shows that while speed is critical, there are situations where users value result quality more than response time. Includes empirical data via log analysis and user surveys, examining user behaviors and perceptions relating to search response time and result quality.

Explores the concept of 'slow search' where speed requirements are relaxed. Shows that while speed is critical, there are situations where users value result quality more than response time. Includes empirical data via log analysis and user surveys, examining user behaviors and perceptions relating to search response time and result quality.

14.6%

0.0

2010

[25] The influence of cognitive load, physical load and system response time on user productivity and satisfaction with computer systems E. Munson and James R. Dabrowski Journal Not Provided 2010 - 0 citations - Show abstract - Cite Abstract: Forty years of research into computer system response time have produced many results but overly-general conclusions. The general consensus is that for various tasks with a computer, faster response times are generally better than slow ones, but the computer can respond too fast. When computer response is too slow, users tend to become annoyed and frustrated with the computer system and may perform their tasks more slowly. When computer response is too fast, users may adapt to this by working faster at the expense of committing more errors and generally feeling more stress. However, only the most general guidelines exist for which tasks require rapid response and those for which the user will tolerate some delay. The present study was undertaken to further determine how specific combinations of mental and physical load contribute to an optimal system response time. A generic data-entry task was systematically manipulated to vary the amount of mental and physical effort a subject experienced when engaged in that task under a variety of delay levels in the hopes of identifying how changes in task difficulty interacted with delay to cause users to perform optimally and be the most satisfied with the system. While changes in task difficulty had a significant impact on several measures of user performance and satisfaction, no interaction was found between various levels of task difficulty and levels of delay with respect to how users performed on the task or how they felt about the system. This calls into question the conventional wisdom in the field that for more difficult tasks, users will tolerate or even prefer longer delays whereas for simpler tasks users will be more sensitive to delays and those delays will have a more significant impact on their performance. In light of these results, a new cost-based model of human-computer interaction is proposed in which delay is viewed as an integral part of the human-computer interaction rather than being viewed as somehow separate from the entire process. 14.6% topic match

Investigates cognitive and physical load impact on system response time. Analyzes how task difficulty and response times affect user productivity and satisfaction. Not specific to online search systems; focuses on generic data-entry tasks.

Investigates cognitive and physical load impact on system response time. Analyzes how task difficulty and response times affect user productivity and satisfaction. Not specific to online search systems; focuses on generic data-entry tasks.

14.4%

1.4

2014

[26] On correlation of absence time and search effectiveness Sunandan Chakraborty, ..., and Paul Baecke Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval 2014 - 14 citations - Show abstract - Cite 14.4% topic match

Paper evaluates: The effectiveness of 'absence time' in measuring user satisfaction. Details: Investigates how absence time relates to user behavior, such as number of queries and clicks on a search engine. Relevance: Focuses on a general metric for user satisfaction, not query response time specifically, making it somewhat distantly related.

Paper evaluates: The effectiveness of 'absence time' in measuring user satisfaction. Details: Investigates how absence time relates to user behavior, such as number of queries and clicks on a search engine. Relevance: Focuses on a general metric for user satisfaction, not query response time specifically, making it somewhat distantly related.

13.9%

1.1

2017

[27] Search Result Prefetching on Desktop and Mobile Ryen W. White, ..., and Qi Guo ACM Transactions on Information Systems (TOIS) 2017 - 8 citations - Show abstract - Cite 13.9% topic match

13.7%

0.1

2014

[28] Too little time?: time constraints and time pressure in information search Anita Crescenzi Proceedings of the 5th Information Interaction in Context Symposium 2014 - 1 citations - Show abstract - Cite 13.7% topic match

13.2%

1.5

2014

[29] What does time constraint mean to information searchers? Chang Liu, ..., and Lu Zhang Proceedings of the 5th Information Interaction in Context Symposium 2014 - 15 citations - Show abstract - Cite 13.2% topic match

Investigates the impact of time constraints on search behavior. Shows how time constraints reduce user confidence and perceived search performance.

Investigates the impact of time constraints on search behavior. Shows how time constraints reduce user confidence and perceived search performance.

12.8%

1.8

2017

[30] Understanding Engagement through Search Behaviour M. Zhuang, ..., and Elaine Toms Proceedings of the 2017 ACM on Conference on Information and Knowledge Management 2017 - 12 citations - Show abstract - Cite 12.8% topic match

12.3%

8.3

2013

[31] How query cost affects search behavior L. Azzopardi, ..., and Kathy Brennan Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval 2013 - 92 citations - Show abstract - Cite - PDF 12.3% topic match

12.1%

3.7

2021

[32] Adaptation in Information Search and Decision-Making under Time Constraints Anita Crescenzi, ..., and Yuan Li Proceedings of the 2021 Conference on Human Information Interaction and Retrieval 2021 - 13 citations - Show abstract - Cite 12.1% topic match

11.7%

2.3

2020

[33] Unravelling the relationship between response time and user experience in mobile applications Mengli Yu, ..., and Huiwen Wang Internet Res. 2020 - 10 citations - Show abstract - Cite 11.7% topic match

11.5%

0.0

2016

[34] Time-Quality Trade-offs in Search Ryan Burton Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval 2016 - 0 citations - Show abstract - Cite 11.5% topic match

11.4%

4.1

2013

[35] Time pressure, user satisfaction and task difficulty Anita Crescenzi, ..., and Jaime Arguello ASIS&T Annual Meeting 2013 - 45 citations - Show abstract - Cite - PDF 11.4% topic match

Explores perceived time pressure's impact on user satisfaction in searching. 269 participants completed 600 tasks, highlighting time pressure as a significant predictor of satisfaction. Does not directly measure search query response time's effect on user behavior.

Explores perceived time pressure's impact on user satisfaction in searching. 269 participants completed 600 tasks, highlighting time pressure as a significant predictor of satisfaction. Does not directly measure search query response time's effect on user behavior.

11.3%

17.8

2012

[36] Time-based calibration of effectiveness measures Mark D. Smucker and C. Clarke Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2012 - 215 citations - Show abstract - Cite 11.3% topic match

Introduces a time-biased gain measure. Examines how different factors influence time spent on search results. Validates against TREC 2005 collection; focuses on time and quality of retrieval, less on query response time specifically.

Introduces a time-biased gain measure. Examines how different factors influence time spent on search results. Validates against TREC 2005 collection; focuses on time and quality of retrieval, less on query response time specifically.

11.1%

2.2

2021

[37] On Latency of E-Commerce Platforms Marcus Basalla, ..., and J. Brocke Journal of Organizational Computing and Electronic Commerce 2021 - 8 citations - Show abstract - Cite 11.1% topic match

10.8%

0.1

2017

[38] Predicting post-task user satisfaction with weibull analysis of task completion times Bernard Rummel Journal of Usability Studies archive 2017 - 1 citations - Show abstract - Cite 10.8% topic match

10.7%

2.0

2016

[39] FOCUS: Shedding light on the high search response time in the wild Dapeng Liu, ..., and Dai Tan IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications 2016 - 17 citations - Show abstract - Cite 10.7% topic match

10.6%

2.6

1997

[40] Internet delay effects: how users perceive quality, organization, and ease of use of information A. Sears, ..., and M. Borella CHI '97 Extended Abstracts on Human Factors in Computing Systems 1997 - 72 citations - Show abstract - Cite - PDF 10.6% topic match

10.5%

0.0

2015

[41] Time Pressure in Information Search Anita Crescenzi Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval 2015 - 0 citations - Show abstract - Cite 10.5% topic match

10.4%

1.6

2015

[42] Behavioral Dynamics from the SERP's Perspective: What are Failed SERPs and How to Fix Them? Julia Kiseleva, ..., and Nikita Makarov Proceedings of the 24th ACM International on Conference on Information and Knowledge Management 2015 - 14 citations - Show abstract - Cite - PDF 10.4% topic match

10.2%

3.9

2016

[43] An Analysis of the Cost and Benefit of Search Interactions L. Azzopardi and G. Zuccon Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval 2016 - 31 citations - Show abstract - Cite - PDF 10.2% topic match

Provides: A formal model of the costs and benefits in search interactions. Details: Analyzes user decisions on query length, specificity, and reformulation. Relevance: Does not explicitly measure query response time's impact on user behavior.

Provides: A formal model of the costs and benefits in search interactions. Details: Analyzes user decisions on query length, specificity, and reformulation. Relevance: Does not explicitly measure query response time's impact on user behavior.

10.2%

5.5

2016

[44] A Context-aware Time Model for Web Search Alexey Borisov, ..., and P. Serdyukov Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval 2016 - 45 citations - Show abstract - Cite - PDF 10.2% topic match

10.1%

0.1

1997

[45] The Effect of Internet Delay on the Perceived Quality of Information A. Sears, ..., and M. Borella Interacción 1997 - 2 citations - Show abstract - Cite 10.1% topic match

9.9%

6.5

2019

[46] Task, Information Seeking Intentions, and User Behavior: Toward A Multi-level Understanding of Web Search Jiqun Liu, ..., and C. Shah Proceedings of the 2019 Conference on Human Information Interaction and Retrieval 2019 - 36 citations - Show abstract - Cite - PDF 9.9% topic match

9.9%

5.0

2017

[47] Effects of task complexity on online search behavior of adolescents J. Walhout, ..., and S. Brand-Gruwel Journal of the Association for Information Science and Technology 2017 - 36 citations - Show abstract - Cite - PDF 9.9% topic match

9.8%

0.4

2010

[48] Human Speed-Accuracy Tradeoffs in Search Christina Aperjis, ..., and Fang Wu 2011 44th Hawaii International Conference on System Sciences 2010 - 6 citations - Show abstract - Cite - PDF 9.8% topic match

Examines user behavior in information foraging on Yahoo Answers. Studies tradeoff between information quality and waiting time in user decision-making. Does not focus on online search systems or measure impact of query response time.

Examines user behavior in information foraging on Yahoo Answers. Studies tradeoff between information quality and waiting time in user decision-making. Does not focus on online search systems or measure impact of query response time.

9.7%

1.2

2015

[49] Load-sensitive CPU Power Management for Web Search Engines Matteo Catena, ..., and N. Tonellotto Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval 2015 - 11 citations - Show abstract - Cite 9.7% topic match

Shows: Investigates CPU power management's impact on web search engine performance. Details: Experiments show up to ~24% power reduction with minimal query processing quality loss using the TREC ClueWeb09 corpus. Relevance: Discusses power management, not focused on query time impact on user behavior; related but not focused on user experience or behavior changes.

Shows: Investigates CPU power management's impact on web search engine performance. Details: Experiments show up to ~24% power reduction with minimal query processing quality loss using the TREC ClueWeb09 corpus. Relevance: Discusses power management, not focused on query time impact on user behavior; related but not focused on user experience or behavior changes.

9.6%

3.0

2005

[50] Consumer Search Behavior in Online Shopping Environments Nanda Kumar, ..., and Qian Peng Proceedings of the 38th Annual Hawaii International Conference on System Sciences 2005 - 59 citations - Show abstract - Cite 9.6% topic match

9.5%

3.5

2005

[51] Need for non-visual feedback with long response times in mobile HCI Virpi Roto and Antti Oulasvirta The Web Conference 2005 - 67 citations - Show abstract - Cite 9.5% topic match

9.4%

2.5

2023

[52] Improving the Effectiveness and Efficiency of Web-Based Search Tasks for Policy Workers T. Schoegje, ..., and T. Pieters Inf. 2023 - 3 citations - Show abstract - Cite - PDF 9.4% topic match

9.3%

6.2

2012

[53] On saliency, affect and focused attention Lori McCay-Peet, ..., and Vidhya Navalpakkam Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 2012 - 77 citations - Show abstract - Cite - PDF 9.3% topic match

9.3%

0.2

2002

[54] The direct and interactive effects of web site delay length, delay variability, and feedback on user attitudes, performance, and intentions D. Galletta and P. Polak Journal Not Provided 2002 - 4 citations - Show abstract - Cite 9.3% topic match

9.2%

1.9

1989

[55] Experimental investigation of stress-inducing properties of system response times. Werner Kuhmann Ergonomics 1989 - 68 citations - Show abstract - Cite 9.2% topic match

Investigates effects of system response times on user stress. Analyzes psychological, subjective, and performance impacts of 2 to 8-second response times. Lacks focus on online search systems and empirical user behavior specific to query response times.

Investigates effects of system response times on user stress. Analyzes psychological, subjective, and performance impacts of 2 to 8-second response times. Lacks focus on online search systems and empirical user behavior specific to query response times.

9.2%

2.0

2018

[56] QWERTY: The Effects of Typing on Web Search Behavior Kevin Ong, ..., and Falk Scholer Proceedings of the 2018 Conference on Human Information Interaction & Retrieval 2018 - 13 citations - Show abstract - Cite - PDF 9.2% topic match

9.1%

0.5

2018

[57] Personalizing Information Retrieval Using Search Behaviors and Time Constraints Chang Liu, ..., and Zengwang Yan Proceedings of the 2018 Conference on Human Information Interaction & Retrieval 2018 - 3 citations - Show abstract - Cite 9.1% topic match

9.0%

23.2

2011

[58] No clicks, no problem: using cursor movements to understand and improve search Jeff Huang, ..., and S. Dumais Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 2011 - 309 citations - Show abstract - Cite 9.0% topic match

8.7%

3.4

2000

[59] The effect of network delay and media on user perceptions of web resources J. Jacko, ..., and M. Borella Behaviour & Information Technology 2000 - 84 citations - Show abstract - Cite 8.7% topic match

8.7%

0.8

2014

[60] Document Prioritization for Scalable Query Processing Hao Wu and Hui Fang Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management 2014 - 8 citations - Show abstract - Cite 8.7% topic match

8.6%

1.5

2016

[61] Prediction and Predictability for Search Query Acceleration Seung-won Hwang, ..., and Seungjin Choi ACM Transactions on the Web (TWEB) 2016 - 12 citations - Show abstract - Cite Abstract: A commercial web search engine shards its index among many servers, and therefore the response time of a search query is dominated by the slowest server that processes the query. Prior approaches target improving responsiveness by reducing the tail latency, or high-percentile response time, of an individual search server. They predict query execution time, and if a query is predicted to be long-running, it runs in parallel; otherwise, it runs sequentially. These approaches are, however, not accurate enough for reducing a high tail latency when responses are aggregated from many servers because this requires each server to reduce a substantially higher tail latency (e.g., the 99.99th percentile), which we call extreme tail latency. To address tighter requirements of extreme tail latency, we propose a new design space for the problem, subsuming existing work and also proposing a new solution space. Existing work makes a prediction using features available at indexing time and focuses on optimizing prediction features for accelerating tail queries. In contrast, we identify “when to predict?” as another key optimization question. This opens up a new solution of delaying a prediction by a short duration to allow many short-running queries to complete without parallelization and, at the same time, to allow the predictor to collect a set of dynamic features using runtime information. This new question expands a solution space in two meaningful ways. First, we see a significant reduction of tail latency by leveraging “dynamic” features collected at runtime that estimate query execution time with higher accuracy. Second, we can ask whether to override prediction when the “predictability” is low. We show that considering predictability accelerates the query by achieving a higher recall. With this prediction, we propose to accelerate the queries that are predicted to be long-running. In our preliminary work, we focused on parallelization as an acceleration scenario. We extend to consider heterogeneous multicore hardware for acceleration. This hardware combines processor cores with different microarchitectures such as energy-efficient little cores and high-performance big cores, and accelerating web search using this hardware has remained an open problem. We evaluate the proposed prediction framework in two scenarios: (1) query parallelization on a multicore processor and (2) query scheduling on a heterogeneous processor. Our extensive evaluation results show that, for both scenarios of query acceleration using parallelization and heterogeneous cores, the proposed framework is effective in reducing the extreme tail latency compared to a start-of-the-art predictor because of its higher recall, and it improves server throughput by more than 70% because of its improved precision. 8.6% topic match

8.4%

6.9

1998

[62] A psychological investigation of long retrieval times on the World Wide Web Judith Ramsay, ..., and J. Preece Interact. Comput. 1998 - 184 citations - Show abstract - Cite 8.4% topic match

8.3%

2.8

2020

[63] The Role of Latency and Task Complexity in Predicting Visual Search Behavior L. Battle, ..., and M. Stonebraker IEEE Transactions on Visualization and Computer Graphics 2020 - 13 citations - Show abstract - Cite 8.3% topic match

8.1%

1.8

2001

[64] The effects of download delay on performance and end-user satisfaction in an Internet tutorial Erica S. Davis and D. Hantula Comput. Hum. Behav. 2001 - 42 citations - Show abstract - Cite 8.1% topic match

8.0%

3.7

2023

[65] The Fast and the Private: Task-based Dataset Search Zezhou Huang, ..., and Eugene Wu ArXiv 2023 - 4 citations - Show abstract - Cite - PDF 8.0% topic match

7.9%

0.6

2017

[66] An Empirical Analysis of Pruning Techniques: Performance, Retrievability and Bias Ruey-Cheng Chen, ..., and Falk Scholer Proceedings of the 2017 ACM on Conference on Information and Knowledge Management 2017 - 4 citations - Show abstract - Cite - PDF 7.9% topic match

7.8%

0.0

2016

[67] Temporal dynamics in information retrieval S. Whiting SIGIR Forum 2016 - 0 citations - Show abstract - Cite Abstract: Since time is an omnipresent feature of our existence, many elements of time are embedded in information itself, and related behaviours such as creation, seeking and utilisation. In IR, time can distinguish the interpretation of information, and influence the intentions and expectations of users' information seeking activity. Many time-based patterns and trends - namely temporal dynamics - are evident in streams of information behaviour by individuals and crowds. A temporal dynamic refers to a periodic regularity, or, a one-off or irregular past, present or future of a particular element (e.g., word, topic or query popularity) - driven by predictable and unpredictable time-based events and phenomena. Several challenges and opportunities related to temporal dynamics emerge in IR. This thesis explores temporal dynamics from the perspective of (i) query popularity and meaning, and (ii) word use and relationships over time. In particular, I consider how real-time temporal dynamics in information seeking should be supported for consistent user satisfaction over time, and moreover, how previously observed temporal dynamics offer a complementary dimension which can be exploited to inform more effective IR systems. Uncertainty about user expectations is a perennial problem for IR systems, further confounded by changes over time. Addressing this, IR systems can either assist the user to submit an effective query (e.g., error-free and descriptive), or better anticipate what the user is most likely to want in relevance ranking. I first explore methods to always help users formulate queries with time-aware query auto-completion capable of suggesting both recent and always popular queries. I propose and evaluate several novel approaches, and demonstrate state-of-the-art performance of up to +9.2% improvement above existing baselines for diverse search scenarios in different languages. Furthermore, I explore the impact of temporal dynamics on the motives behind users' information seeking, and thus how relevance itself is subject to temporal dynamics. I find the most likely meaning of ambiguous queries is affected over short and long-term periods (e.g., hours to months) by several periodic and oneoff event-driven temporal dynamics. Finally, I find that for many event-driven multi-faceted queries, relevance can often be inferred by modelling the temporal dynamics of changes in related information. IR approaches are typically based on methods which characterize the nature of information through the statistical distributions of words and phrases. I model and exploit the temporal dimension of the collection, captured by temporal dynamics, in these established IR approaches. I explore how the temporal dynamic similarity of word and phrase use in a collection can be exploited to infer temporal semantic relationships between the terms. I propose an approach to uncover a query topic's "chronotype" terms -- that is, its most distinctive and temporally interdependent terms, based on a mix of temporal and non-temporal evidence. Experiments demonstrate that exploiting chronotype terms in temporal query expansion leads to significantly improved retrieval performance in several time-based collections. Temporal dynamics provide both a challenge and an opportunity for IR systems. Overall, this thesis demonstrates that temporal dynamics can be used to derive tacit structure and meaning of information and information behaviour, which is valuable for improving timeaware IR system effectiveness. 7.8% topic match

7.8%

0.3

2017

[68] Exploring and understanding web search behavior with human activities Shuang-shou Li, ..., and Yaoxue Zhang 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) 2017 - 2 citations - Show abstract - Cite 7.8% topic match

7.7%

31.7

2005

[69] Evaluating implicit measures to improve web search Steve Fox, ..., and Thomas White ACM Trans. Inf. Syst. 2005 - 616 citations - Show abstract - Cite 7.7% topic match

7.4%

6.9

2012

[70] Large-scale analysis of individual and task differences in search result page examination strategies Georg Buscher, ..., and Jeff Huang Web Search and Data Mining 2012 - 87 citations - Show abstract - Cite - PDF 7.4% topic match

7.4%

1.1

2016

[71] Using Crowd Sourcing to Measure the Effects of System Response Delays on User Engagement Brandon T. Taylor, ..., and A. Smailagic Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems 2016 - 9 citations - Show abstract - Cite 7.4% topic match

7.1%

1.6

2012

[72] Ordinary search engine users assessing difficulty, effort, and outcome for simple and complex search tasks Georg Singer, ..., and D. Lewandowski ArXiv 2012 - 20 citations - Show abstract - Cite - PDF 7.1% topic match

7.1%

2.3

2020

[73] How searching under time pressure impacts clinical decision making A. van der Vegt, ..., and Anthony J Deacon Journal of the Medical Library Association : JMLA 2020 - 9 citations - Show abstract - Cite - PDF 7.1% topic match

7.0%

0.7

2014

[74] The influence of task type on search experience from the perspective of time constraint Chang Liu, ..., and Yu Zhao ASIS&T Annual Meeting 2014 - 7 citations - Show abstract - Cite - PDF 7.0% topic match

7.0%

0.0

2024

[75] Understanding users' dynamic perceptions of search gain and cost in sessions: An expectation confirmation model Ben Wang and Jiqun Liu Journal of the Association for Information Science and Technology 2024 - 0 citations - Show abstract - Cite 7.0% topic match

6.9%

0.0

2018

[76] Adopting a graphical perspective in interactive information retrieval research M. Mitsui https://doi.org/10.7282/T3-PG46-Y768 2018 - 0 citations - Show abstract - Cite 6.9% topic match

6.9%

4.2

2013

[77] Evaluating and predicting user engagement change with degraded search relevance Yang Song, ..., and Xin Fu Proceedings of the 22nd international conference on World Wide Web 2013 - 47 citations - Show abstract - Cite 6.9% topic match

6.9%

1.2

2016

[78] Search Result Prefetching Using Cursor Movement Fernando Diaz, ..., and Ryen W. White Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval 2016 - 10 citations - Show abstract - Cite 6.9% topic match

6.8%

2.3

2022

[79] Searching, Learning, and Subtopic Ordering: A Simulation-based Analysis A. Câmara, ..., and C. Hauff European Conference on Information Retrieval 2022 - 6 citations - Show abstract - Cite - PDF 6.8% topic match

6.7%

10.5

1998

[80] How Tolerable is Delay? Consumers’ Evaluations of Internet Web Sites after Waiting B. Dellaert and B. Kahn Journal Not Provided 1998 - 279 citations - Show abstract - Cite 6.7% topic match

6.7%

16.4

2010

[81] Beyond DCG: user behavior as a predictor of a successful search Ahmed Hassan Awadallah, ..., and K. Klinkner Web Search and Data Mining 2010 - 240 citations - Show abstract - Cite 6.7% topic match

6.5%

9.4

2010

[82] Personalized click prediction in sponsored search H. Cheng and E. Cantú-Paz Web Search and Data Mining 2010 - 137 citations - Show abstract - Cite - PDF 6.5% topic match

6.5%

6.8

2011

[83] 40 Years of Searching for the Best Computer System Response Time James R. Dabrowski and E. Munson Interact. Comput. 2011 - 88 citations - Show abstract - Cite 6.5% topic match

6.3%

0.3

2013

[84] Incorporating Efficiency in Evaluation E. Kharitonov, ..., and P. Serdyukov Journal Not Provided 2013 - 4 citations - Show abstract - Cite 6.3% topic match

6.2%

0.8

2017

[85] Time Limits, Information Search and the Use of Search Assistance Anita Crescenzi, ..., and Jaime Arguello Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval 2017 - 6 citations - Show abstract - Cite 6.2% topic match

6.2%

13.1

2004

[86] Web Site Delays: How Tolerant are Users? D. Galletta, ..., and P. Polak J. Assoc. Inf. Syst. 2004 - 272 citations - Show abstract - Cite - PDF 6.2% topic match

5.9%

1.0

2021

[87] Authentic versus synthetic: An investigation of the influences of study settings and task configurations on search behaviors Yiwei Wang and C. Shah Journal of the Association for Information Science and Technology 2021 - 3 citations - Show abstract - Cite 5.9% topic match

5.9%

0.4

2016

[88] ERWIN - enabling the reproducible investigation of waiting times for arbitrary workflows T. Zinner, ..., and O. Hohlfeld 2016 Eighth International Conference on Quality of Multimedia Experience (QoMEX) 2016 - 3 citations - Show abstract - Cite 5.9% topic match

5.8%

1.8

2021

[89] AutoSens: inferring latency sensitivity of user activity through natural experiments Parth Thakkar, ..., and V. Padmanabhan Proceedings of the 21st ACM Internet Measurement Conference 2021 - 5 citations - Show abstract - Cite 5.8% topic match

5.7%

4.8

2014

[90] CiteSight: supporting contextual citation recommendation using differential search Avishay Livne, ..., and Eytan Adar Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval 2014 - 49 citations - Show abstract - Cite 5.7% topic match

5.6%

0.2

2012

[91] A user study of web search session behaviour using eye tracking data Mari-Carmen Marcos, ..., and Diego Sáez-Trumper British Computer Society Conference on Human-Computer Interaction 2012 - 2 citations - Show abstract - Cite - PDF 5.6% topic match

5.6%

1.7

2017

[92] Asking "Good" Questions: Questionnaire Design and Analysis in Interactive Information Retrieval Research H. O'Brien and Lori McCay-Peet Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval 2017 - 13 citations - Show abstract - Cite 5.6% topic match

5.5%

0.0

2016

[93] The Effects of Latency on 3D Interactive Data Visualizations A. Korenevsky https://doi.org/10.15368/theses.2016.37 2016 - 0 citations - Show abstract - Cite 5.5% topic match

5.4%

7.4

2020

[94] Exploring Users' Learning Gains within Search Sessions Nirmal Roy, ..., and C. Hauff Proceedings of the 2020 Conference on Human Information Interaction and Retrieval 2020 - 33 citations - Show abstract - Cite 5.4% topic match

5.3%

2.1

2012

[95] Situation Normality and the Shape of Search: The Effects of Time Delays and Information Presentation on Search Behavior Nolan J. Taylor, ..., and Jeff W. Cummings Cognition & the Arts eJournal 2012 - 25 citations - Show abstract - Cite - PDF 5.3% topic match

5.3%

55.0

2004

[96] Understanding user goals in web search Daniel E. Rose and D. Levinson The Web Conference 2004 - 1118 citations - Show abstract - Cite - PDF 5.3% topic match

5.2%

51.1

2019

[97] Improving Web Search Ranking by Incorporating User Behavior Information Eugene Agichtein, ..., and S. Dumais ACM SIGIR Forum 2019 - 288 citations - Show abstract - Cite 5.2% topic match

5.2%

1.3

2017

[98] Adaptive Persistence for Search Effectiveness Measures Jiepu Jiang and James Allan Proceedings of the 2017 ACM on Conference on Information and Knowledge Management 2017 - 9 citations - Show abstract - Cite 5.2% topic match

5.1%

0.2

2006

[99] Understanding the Direct and Interaction Effects of Web Delay and Related Factors D. Galletta, ..., and P. Polak Journal Not Provided 2006 - 3 citations - Show abstract - Cite Abstract: The benefits of using the Internet are partially offset by one aspect of its usability: highly variable, intermittent, but frequent inter-page delay. For several years, the HCI literature has studied user reactions to long computer response time in clerical applications, but few studies have examined this problem in the domain of the Web. Examining the delay problem in a Web context is important, because the Web touches many more users, most of whom have little formal computer or task training. Hence, we have examined in our labs consequences of delay, along with factors that interact with delay. Some of our experiments have been published and some are still under review. Consequences of delay that we examined include user attitudes, behavior, and performance. Factors that we examined for possible interactions included site depth, familiarity with terminology used in organizing the site, variability of the delay, and feedback (continuous and gradual filling of the screen to make it obvious that the page is indeed loading). Experiment 1 (n 196) provided seven levels of delay, ranging from zero to twelve seconds (in two-second increments), and discovered that ill effects began as delay exceeded two seconds. Experiment 2 (n 206) again compared reactions to the same levels of delay, but this time with Mexican subjects. It was found that Mexicans were more patient than subjects in the United States. In both studies, the outcomes differed when comparing a familiar site with an unfamiliar site, suggesting that interactions should be examined more formally. Experiment 3 (n 160) introduced two other factors from the HCI literature, and with a 2 2 2 ANOVA, we assessed the interactions between delay, site depth, and familiarity with the terminology in the site. As predicted, we found a significant three-way interaction. Consistent with more traditional literature, we also found strong direct effects. Experiment 4 (n 152) employed another 2 2 2 design, but along with delay we analyzed the effects of variability and feedback as interacting variables. Analysis revealed that page-loading feedback is only important when there are long delays, and variability does not seem to be important in influencing attitudes, behavior, and performance of users. Conclusions from the four studies are that user impatience is high; that the results of delay can differ with culture; and that the variables that interact with delay are familiarity with site terminology, depth of the site, and feedback (in a slow site). Variability does not seem to interact with delay. 5.1% topic match

5.1%

2.7

2006

[100] Information foraging on the web: The effects of "acceptable" Internet delays on multi-page information search behavior A. Dennis and Nolan J. Taylor Decis. Support Syst. 2006 - 48 citations - Show abstract - Cite 5.1% topic match

5.0%

4.8

2018

[101] "Satisfaction with Failure" or "Unsatisfied Success": Investigating the Relationship between Search Success and User Satisfaction Mengyang Liu, ..., and Shaoping Ma Proceedings of the 2018 World Wide Web Conference 2018 - 31 citations - Show abstract - Cite - PDF 5.0% topic match

4.9%

0.1

2010

[102] Intelligent user search behaviour knowledge discovery Yun Shen and T. Martin International Conference on Fuzzy Systems 2010 - 1 citations - Show abstract - Cite 4.9% topic match

4.9%

4.6

2020

[103] Providing Direct Answers in Search Results: A Study of User Behavior Zhijing Wu, ..., and Falk Scholer Proceedings of the 29th ACM International Conference on Information & Knowledge Management 2020 - 18 citations - Show abstract - Cite 4.9% topic match

4.8%

0.6

2016

[104] A longitudinal study of information needs and search behaviors in science and technology: A query analysis Minsoo Park and Taeseok Lee Electron. Libr. 2016 - 5 citations - Show abstract - Cite 4.8% topic match

4.7%

1.1

2003

[105] Examining Tolerance for Online Delays B. Chaparro and P. Selvidge Journal Not Provided 2003 - 24 citations - Show abstract - Cite Abstract: The World Wide Web (WWW) has become an increasingly important medium for communication,commerce, and entertainment. The WWW user population is estimated to grow to 320 million by theyear 2002 (Bouch et al., 2000). The 10th WWW User Survey reported that speed, or taking too long todownload pages, was the third major problem with the Internet reported by users (GVU, 1998). Thisproblem translates into lost profits for e-commerce websites due to effects on users� perceptions andperformance. ZDNet (2002) reported a study of 12,000 online customers that revealed 48% of themgave up trying to purchase products because the web pages took too long to download. Brynijolfssonand Smith (2000) pointed out that trust is probably the single most important factor in e-commerce andthe effects of time delay can significantly reduce consumer trust towards an e-commerce retailer.Unfortunately, addressing the factors that affect download time is not as simple as making hardwareimprovements. Since problems with delays are expected to persist, the effects of delays on aspects ofwebsite usability remain an important concern and are the focus of this study.In this study, user tolerance for delays for three common WWW tasks, including information retrieval, purchasing, and downloading a text file was examined. These tasks were selected since the file sizes differ significantly among the three tasks, so it was expected that tolerance may be higher for those tasks with smaller file sizes. For example, tolerance for delays would be higher for downloading a text file than purchasing or information retrieval, since users may have an expectation that the task should take longer so they may be more willing to wait. End-users may be more tolerant of delays while purchasing online, since information must be exchanged to process the transaction, whereas information retrieval does not require information exchange. The general purpose of this study was to examine how long participants would wait for web pages to load before abandoning a website. Previous research has primarily examined the effect of delays on preference and subjective evaluations of websites, but has failed to focus on the most important aspect,which is end-user behavior. The important question for e-commerce organizations is when will the potential customer leave the website because the wait is too long. The effects of different demographiccharacteristics, such as age (young adults/older adults), Internet experience level (novice/experienced),and type of Internet connection frequently used on tolerance for delays relating to three types of common Internet tasks (information retrieval, purchasing, downloading a text file) were investigated. It was hypothesized that (i) older adults would be more tolerant of delays than younger adults, (ii) participants with more Internet experience would be less tolerant of delays than novice users, (iii) participants would be more tolerant of delays for tasks involving downloading text files than purchasing or information retrieval tasks, and (iv) participants that frequently use high-speed connections to the Internet, e.g. cable or DSL modems, would be less tolerant of delays. 4.7% topic match

4.7%

0.0

2017

[106] Well-Balanced Successive Simple-9 for Inverted Lists Compression Kun Jiang, ..., and Qi-chuan Zheng IEICE Trans. Inf. Syst. 2017 - 0 citations - Show abstract - Cite 4.7% topic match

4.7%

0.8

2009

[107] Take your time first, time your search later: How college students perceive time in Web searching Shu-Yi Chen and Soo Young Rieh ASIS&T Annual Meeting 2009 - 13 citations - Show abstract - Cite - PDF 4.7% topic match

4.6%

0.4

2011

[108] The Effect of Feedback on Web Site Delay: A Perceptual and Physiological Study Hong Sheng and Nicholas S. Lockwood Journal Not Provided 2011 - 6 citations - Show abstract - Cite 4.6% topic match

4.6%

3.0

2015

[109] Using physiological sensors to detect levels of user frustration induced by system delays Brandon T. Taylor, ..., and A. Smailagic Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing 2015 - 27 citations - Show abstract - Cite 4.6% topic match

4.5%

1.1

2019

[110] Coagmento v3.0: Rapid Prototyping of Web Search Experiments Diana Soltani, ..., and C. Shah Proceedings of the 2019 Conference on Human Information Interaction and Retrieval 2019 - 6 citations - Show abstract - Cite - PDF 4.5% topic match

4.5%

0.1

2016

[111] Preliminary exploration of the effect of time constraint on search interactions on webpages Chang Liu and Tao Xu 2016 IEEE/ACM Joint Conference on Digital Libraries (JCDL) 2016 - 1 citations - Show abstract - Cite 4.5% topic match

4.5%

9.7

2014

[112] Modelling interaction with economic models of search L. Azzopardi Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval 2014 - 99 citations - Show abstract - Cite - PDF 4.5% topic match

4.4%

3.2

2012

[113] Prefetching query results and its impact on search engines Simon Jonassen, ..., and F. Silvestri Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2012 - 39 citations - Show abstract - Cite - PDF 4.4% topic match

4.3%

4.9

2021

[114] Query Suggestions as Summarization in Exploratory Search A. Medlar, ..., and D. Głowacka Proceedings of the 2021 Conference on Human Information Interaction and Retrieval 2021 - 17 citations - Show abstract - Cite 4.3% topic match

4.3%

25.7

2006

[115] Improving web search ranking by incorporating user behavior information Eugene Agichtein, ..., and S. Dumais Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval 2006 - 465 citations - Show abstract - Cite 4.3% topic match

4.2%

1.2

2010

[116] The Effects of Query Bursts on Web Search Ilija Subasic and C. Castillo 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology 2010 - 17 citations - Show abstract - Cite - PDF 4.2% topic match

4.2%

3.4

2006

[117] Web search clickstreams Nils Kammenhuber, ..., and G. Weikum ACM/SIGCOMM Internet Measurement Conference 2006 - 60 citations - Show abstract - Cite - PDF 4.2% topic match

4.2%

0.3

2017

[118] Luo, Cheng and Liu, Yiqun and Sakai, Tetsuya and Zhou, Ke and Zhang, Fan and Li, Xue and Ma, Shaoping (2017) Does document relevance affect the searcher's perception 0f time? In: 10th ACM International Conference on Web Search and Data No author found Journal Not Provided 2017 - 2 citations - Show abstract - Cite 4.2% topic match

4.2%

4.3

2012

[119] Exploring and predicting search task difficulty Jingjing Liu, ..., and Xiangmin Zhang Proceedings of the 21st ACM international conference on Information and knowledge management 2012 - 51 citations - Show abstract - Cite 4.2% topic match

4.1%

0.9

2017

[120] Does Document Relevance Affect the Searcher's Perception of Time? Cheng Luo, ..., and Shaoping Ma Proceedings of the Tenth ACM International Conference on Web Search and Data Mining 2017 - 7 citations - Show abstract - Cite - PDF 4.1% topic match

4.1%

6.8

2012

[121] Learning to predict response times for online query scheduling Craig Macdonald, ..., and I. Ounis Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2012 - 82 citations - Show abstract - Cite - PDF 4.1% topic match

4.1%

0.1

2010

[122] Grössere Zufriedenheit durch bessere Suchmaschinen?: Das Confirmation/Disconfirmation-Paradigma der Kundenzufriedenheit im Kontext des Information Retrieval K. Werner Journal Not Provided 2010 - 1 citations - Show abstract - Cite 4.1% topic match

3.9%

0.4

2017

[123] Managing Tail Latencies in Large Scale IR Systems J. Mackenzie Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval 2017 - 3 citations - Show abstract - Cite Abstract: With the growing popularity of the world-wide-web and the increasing accessibility of smart devices, data is being generated at a faster rate than ever before. This presents scalability challenges to web-scale search systems -- how can we efficiently index, store and retrieve such a vast amount of data? A large amount of prior research has attempted to address many facets of this question, with the invention of a range of efficient index storage and retrieval frameworks that are able to efficiently answer most queries. However, the current literature generally focuses on improving the mean or median query processing time in a given system. In the proposed PhD project, we focus on improving the efficiency of high percentile tail latencies in large scale IR systems while minimising end-to-end effectiveness loss. Although there is a wealth of prior research involving improving the efficiency of large scale IR systems, the most relevant prior work involves predicting long-running queries and processing them in various ways to avoid large query processing times. Prediction is often done through pre-trained models based on both static and dynamic features from queries and documents. Many different approaches to reducing the processing time of long running queries have been proposed, including parallelising queries that are predicted to run slowly, scheduling queries based on their predicted run time, and selecting or modifying the query processing algorithm depending on the load of the system. Considering the specific focus on tail latencies in large-scale IR systems, the proposed research aims to: (i) study what causes large tail latencies to occur in large-scale web search systems, (ii) propose a framework to mitigate tail latencies in multi-stage retrieval through the prediction of a vast range of query-specific efficiency parameters, (iii) experiment with mixed-mode query semantics to provide efficient and effective querying to reduce tail latencies, and (iv) propose a time-bounded solution for Document-at-a-Time (DaaT) query processing which is suitable for current web search systems. As a preliminary study, Crane et al. compared some state-of-the-art query processing strategies across many modern collections. They found that although modern DaaT dynamic pruning strategies are very efficient for ranked disjunctive processing, they have a much larger variance in processing times than Score-at-a-Time (SaaT) strategies which have a similar efficiency profile regardless of query length or the size of the required result set. Furthermore, Mackenzie et al. explored the efficiency trade-offs for paragraph retrieval in a multi-stage question answering system. They found that DaaT dynamic pruning strategies could efficiently retrieve the top-1,000 candidate paragraphs for very long queries. Extending on prior work, Mackenzie et al. showed how a range of per-query efficiency settings can be accurately predicted such that 99.99 percent of queries are serviced in less than 200 ms without noticeable effectiveness loss. In addition, a reference list framework was used for training models such that no relevance judgements or annotations were required. Future work will focus on improving the candidate generation stage in large-scale multi-stage retrieval systems. This will include further exploration of index layouts, traversal strategies, and query rewriting, with the aim of improving early stage efficiency to reduce the system tail latency, while potentially improving end-to-end effectiveness. 3.9% topic match

3.9%

0.5

2010

[124] Search Engine User Behavior Analysis Based on Log Mining Ma Shao-ping Journal of Chinese information processing 2010 - 7 citations - Show abstract - Cite 3.9% topic match

3.9%

4.4

2020

[125] Examining the Additivity of Top-k Query Processing Innovations J. Mackenzie and Alistair Moffat Proceedings of the 29th ACM International Conference on Information & Knowledge Management 2020 - 17 citations - Show abstract - Cite 3.9% topic match

3.8%

1.6

2017

[126] Personalised Search Time Prediction using Markov Chains V. Tran, ..., and L. Azzopardi Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval 2017 - 11 citations - Show abstract - Cite - PDF 3.8% topic match

3.8%

2.9

2016

[127] The impacts of time constraint on users' search strategy during search process Chang Liu and Yiming Wei Proceedings of the Association for Information Science and Technology 2016 - 23 citations - Show abstract - Cite - PDF 3.8% topic match

3.7%

2.0

2018

[128] Information Scent, Searching and Stopping - Modelling SERP Level Stopping Behaviour David Maxwell and L. Azzopardi European Conference on Information Retrieval 2018 - 13 citations - Show abstract - Cite - PDF 3.7% topic match

3.6%

11.4

2001

[129] Optimizing search by showing results in context S. Dumais, ..., and Haoyu Chen Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 2001 - 269 citations - Show abstract - Cite 3.6% topic match

3.6%

2.0

2015

[130] An Initial Investigation into Fixed and Adaptive Stopping Strategies David Maxwell, ..., and Heikki Keskustalo Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval 2015 - 18 citations - Show abstract - Cite - PDF 3.6% topic match

3.6%

0.0

2017

[131] PRIOR STUDIES ON IIR SIMULATION 2 . 1 Common Interaction Model T. Pääkkönen, ..., and K. Järvelin Journal Not Provided 2017 - 0 citations - Show abstract - Cite 3.6% topic match

3.6%

1.1

2019

[132] Impact of a Search Engine on Clinical Decisions Under Time and System Effectiveness Constraints: Research Protocol A. van der Vegt, ..., and Anthony J Deacon JMIR Research Protocols 2019 - 6 citations - Show abstract - Cite - PDF Abstract: Background Many clinical questions arise during patient encounters that clinicians are unable to answer. An evidence-based medicine approach expects that clinicians will seek and apply the best available evidence to answer clinical questions. One commonly used source of such evidence is scientific literature, such as that available through MEDLINE and PubMed. Clinicians report that 2 key reasons why they do not use search systems to answer questions is that it takes too much time and that they do not expect to find a definitive answer. So, the question remains about how effectively scientific literature search systems support time-pressured clinicians in making better clinical decisions. The results of this study are important because they can help clinicians and health care organizations to better assess their needs with respect to clinical decision support (CDS) systems and evidence sources. The results and data captured will contribute a significant data collection to inform the design of future CDS systems to better meet the needs of time-pressured, practicing clinicians. Objective The purpose of this study is to understand the impact of using a scientific medical literature search system on clinical decision making. Furthermore, to understand the impact of realistic time pressures on clinicians, we vary the search time available to find clinical answers. Finally, we assess the impact of improvements in search system effectiveness on the same clinical decisions. Methods In this study, 96 practicing clinicians and final year medical students are presented with 16 clinical questions which they must answer without access to any external resource. The same questions are then represented to the clinicians; however, in this part of the study, the clinicians can use a scientific literature search engine to find evidence to support their answers. The time pressures of practicing clinicians are simulated by limiting answer time to one of 3, 6, or 9 min per question. The correct answer rate is reported both before and after search to assess the impact of the search system and the time constraint. In addition, 2 search systems that use the same user interface, but which vary widely in their search effectiveness, are employed so that the impact of changes in search system effectiveness on clinical decision making can also be assessed. Results Recruiting began for the study in June 2018. As of the April 4, 2019, there were 69 participants enrolled. The study is expected to close by May 30, 2019, with results to be published in July. Conclusions All data collected in this study will be made available at the University of Queensland’s UQ eSpace public data repository. International Registered Report Identifier (IRRID) DERR1-10.2196/12803 3.6% topic match

3.5%

0.9

2012

[133] Exploration of dynamic query suggestions and dynamic search results for their effects on search behaviors C. Shah, ..., and N. Belkin ASIS&T Annual Meeting 2012 - 12 citations - Show abstract - Cite 3.5% topic match

3.5%

0.3

2012

[134] Study of result presentation and interaction for aggregated search Shanu Sushmita SIGIR Forum 2012 - 4 citations - Show abstract - Cite Abstract: "Searching" on web has become an integral part of today's world, and many people rely on it when looking for information. The amount and the diversity of information available on the Web have also increased dramatically. Due to which, search engine companies are making constant efforts in order to make this information accessible to the people effectively. Not only there is an increase in the amount and diversity of information available online, users are now often seeking information on broader topics. Users seeking information on broad topics, gather information from various information sources (e.g., image, video, news, blog, etc). For such information requests, not only web results but results from different document genre and multimedia contents are also becoming relevant. For instance, users' looking for information on "Glasgow" might be interested in web results about Glasgow, Map of Glasgow, Images of Glasgow, News of Glasgow, and so on. Aggregated search aims to provide access to this diverse information in a unified manner by aggregating results from different information sources on a single result page; hence making information gathering process easier for broad topics. This thesis aimed to explore aggregated search from the users perspective. The thesis first and foremost focused on understanding and describing the phenomena related to the users' search process in the context of aggregated search. The goal was to participate in building theories and in understanding constraints, as well as providing insights into the interface design. While the thematic (or topical) relevance of documents is important, this thesis argued that the "source type" (source-orientation) might also be an important dimension in the relevance space for investigating aggregated search. Therefore, relevance is multi-dimensional (topical and sourceorientated) within the context of aggregated search. Results from the study suggested that the effect of the source-orientation was a significant factor in an aggregated search scenario, hence adding another dimension to the relevance space within the aggregated search scenario. The thesis further presented a method, which combines rule base and machine learning techniques to identify source-orientation behind a user query. Furthermore, after analyzing log data from a search engine company and conducting user study experiments, several design issues that may arise with respect to the aggregated search interface were identified. In order to address these issues, suitable design guidelines that can be beneficial from the interface perspective were also suggested. Overall, the thesis aimed to explore the emerging aggregated search from users' perspective, since it is a very important for front-end technologies. An additional goal was to provide empirical evidence regarding how aggregated search influence users searching behavior, and identified some of the key challenges in aggregated search. Available online at: http://theses.gla.ac.uk/3289/. 3.5% topic match

3.4%

15.8

2010

[135] How does search behavior change as search becomes more difficult? A. Aula, ..., and Z. Guan Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 2010 - 228 citations - Show abstract - Cite 3.4% topic match

3.4%

2.9

2009

[136] Efficiency trade-offs in two-tier web search systems R. Baeza-Yates, ..., and C. Hauff Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval 2009 - 44 citations - Show abstract - Cite - PDF 3.4% topic match

3.4%

0.4

2001

[137] Brewsing the web: delay, determination and satisfaction F. Culwin and X. Faulkner Proceedings of the 34th Annual Hawaii International Conference on System Sciences 2001 - 9 citations - Show abstract - Cite 3.4% topic match

3.4%

3.0

2013

[138] When Filling the Wait Makes it Feel Longer: A Paradigm Shift Perspective for Managing Online Delay Weiyin Hong, ..., and Andrew M. Hardin MIS Q. 2013 - 34 citations - Show abstract - Cite 3.4% topic match

3.4%

1.6

2004

[139] Research in Search Engine User Behavior Based on Log Analysis Huijia Yu, ..., and Shaoping Ma Journal of Chinese information processing 2004 - 34 citations - Show abstract - Cite 3.4% topic match

3.3%

1.7

2014

[140] Time well spent C. Clarke and Mark D. Smucker Proceedings of the 5th Information Interaction in Context Symposium 2014 - 17 citations - Show abstract - Cite 3.3% topic match

3.3%

7.9

2015

[141] How many results per page?: A Study of SERP Size, Search Behavior and User Experience D. Kelly and L. Azzopardi Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval 2015 - 72 citations - Show abstract - Cite 3.3% topic match

3.3%

0.5

2016

[142] Using the Crowd to Improve Search Result Ranking and the Search Experience Yubin Kim, ..., and J. Teevan ACM Transactions on Intelligent Systems and Technology (TIST) 2016 - 4 citations - Show abstract - Cite 3.3% topic match

3.2%

4.0

2019

[143] The effects of perceived chronic pressure and time constraint on information search behaviors and experience Chang Liu, ..., and Fan Yang Inf. Process. Manag. 2019 - 20 citations - Show abstract - Cite 3.2% topic match

3.1%

53.9

2010

[144] The development and evaluation of a survey to measure user engagement H. O'Brien and Elaine Toms J. Assoc. Inf. Sci. Technol. 2010 - 792 citations - Show abstract - Cite - PDF 3.1% topic match

3.1%

0.6

2019

[145] Comprehensive Characterization of an Open Source Document Search Engine Zacharias Hadjilambrou, ..., and Yiannakis Sazeides ACM Transactions on Architecture and Code Optimization (TACO) 2019 - 3 citations - Show abstract - Cite - PDF 3.1% topic match

3.1%

11.8

2006

[146] Boosting the performance of Web search engines: Caching and prefetching query results by exploiting historical usage data T. Fagni, ..., and S. Orlando ACM Trans. Inf. Syst. 2006 - 221 citations - Show abstract - Cite 3.1% topic match

3.1%

3.5

2019

[147] Investigating the role of eye movements and physiological signals in search satisfaction prediction using geometric analysis Yingying Wu, ..., and S. Yau Journal of the Association for Information Science and Technology 2019 - 18 citations - Show abstract - Cite 3.1% topic match

3.1%

0.0

2016

[148] Building Realistic Simulations for Interactive Information Retrieval David Maxwell Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval 2016 - 0 citations - Show abstract - Cite 3.1% topic match

3.0%

3.2

2016

[149] Using Navigation to Improve Recommendations in Real-Time Chao-Yuan Wu, ..., and J. Basilico Proceedings of the 10th ACM Conference on Recommender Systems 2016 - 26 citations - Show abstract - Cite - PDF 3.0% topic match

3.0%

0.1

2004

[150] The effect of system response time on visual search in Web pages P. Schaik and Jonathan Ling Electron. Libr. 2004 - 3 citations - Show abstract - Cite 3.0% topic match

3.0%

3.4

2020

[151] Search Result Explanations Improve Efficiency and Trust Jerome Ramos and Carsten Eickhoff Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval 2020 - 14 citations - Show abstract - Cite 3.0% topic match

2.9%

0.2

2018

[152] Correlation Based Evaluation for Search Tools R. K. Goutam 2018 5th International Conference on Signal Processing and Integrated Networks (SPIN) 2018 - 1 citations - Show abstract - Cite 2.9% topic match

2.9%

6.4

2017

[153] Meta-evaluation of Online and Offline Web Search Evaluation Metrics Ye Chen, ..., and Shaoping Ma Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval 2017 - 45 citations - Show abstract - Cite 2.9% topic match

2.9%

2.2

2010

[154] Comparing web interaction models in developing regions Jay Chen, ..., and L. Subramanian https://doi.org/10.1145/1926180.1926188 2010 - 30 citations - Show abstract - Cite - PDF 2.9% topic match

2.9%

0.9

2020

[155] Untangling Header Bidding Lore Some myths, some truths, and some hope Waqar Aqeel, ..., and Ankit Singla Journal Not Provided 2020 - 4 citations - Show abstract - Cite 2.9% topic match

2.8%

1.0

2019

[156] Deep Learning of Human Information Foraging Behavior with a Search Engine Xi Niu and Xiangyu Fan Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval 2019 - 5 citations - Show abstract - Cite 2.8% topic match

2.8%

5.5

2003

[157] Culture and consumer responses to web download time: a four-continent study of mono and polychronism G. Rose, ..., and D. Straub IEEE Trans. Engineering Management 2003 - 118 citations - Show abstract - Cite 2.8% topic match

2.8%

4.3

2009

[158] The role of subjective factors in the information search process J. Gwizdka and Irene Lopatovska J. Assoc. Inf. Sci. Technol. 2009 - 68 citations - Show abstract - Cite - PDF 2.8% topic match

2.8%

96.5

2017

[159] The QUIC Transport Protocol: Design and Internet-Scale Deployment Adam Langley, ..., and Z. Shi Proceedings of the Conference of the ACM Special Interest Group on Data Communication 2017 - 684 citations - Show abstract - Cite - PDF 2.8% topic match

2.7%

0.7

2023

[160] Defining 'seamlessly connected': user perceptions of operation latency in cross-device interaction Xinze Liu, ..., and Yan Ge Int. J. Hum. Comput. Stud. 2023 - 1 citations - Show abstract - Cite 2.7% topic match

2.7%

1.1

2017

[161] An ant-colony based approach for real-time implicit collaborative information seeking A. Malizia, ..., and P. Crescenzi Inf. Process. Manag. 2017 - 8 citations - Show abstract - Cite - PDF 2.7% topic match

2.7%

3.8

2014

[162] Modeling action-level satisfaction for search task satisfaction prediction Hongning Wang, ..., and Ryen W. White Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval 2014 - 39 citations - Show abstract - Cite - PDF 2.7% topic match

2.6%

0.6

2017

[163] Designing a Survey Tool for Monitoring Enterprise QoE Kathrin Borchert, ..., and A. Göritz Proceedings of the Workshop on QoE-based Analysis and Management of Data Communication Networks 2017 - 4 citations - Show abstract - Cite 2.6% topic match

2.6%

0.0

2020

[164] RE-EXAMINING THE ROLE OF TIME IN HUMAN-ALGORITHM INTERACTION BY Professor Karrie Karahalios Journal Not Provided 2020 - 0 citations - Show abstract - Cite Abstract: How fast we interact with technology has been one of the most salient topics for both the users and designers of computing systems. Experimental results since the days preceding personal computing era characterized short response time as an agent for user satisfaction, productivity, and engagement, and we have invested a signiﬁcant amount of engineering eﬀort to make our computers faster ever since. However, the role of speed in human-computer interaction is much richer and more multi-faceted than what today’s culture of moving fast makes it out to be; where faster interaction oﬀers us eﬃciency, slower interaction oﬀers us a chance for reﬂection, serendipity, and a moment for deliberate thinking. As we transition into the days of advanced algorithms and AI where even the most consequential and often problematic judgments are made on our behalf, I see an opportunity to revisit our belief in speed, and examine what slowing down can do to empower users in the interaction between humans and algorithms. To this end, this thesis explores concrete, measurable beneﬁts of slower interaction in improving users’ assessment of an algorithm’s accuracy in human-algorithm interaction. Speciﬁcally, I report a series of online and in-person between-subject user studies in which I isolate the impact of an algorithm’s speed on how users incorporate the algorithm’s advice when making judgments in the context of simple visual recognition tasks. I ﬁnd that the participants followed good quality algorithms more and bad quality algorithms somewhat less if the response time of the algorithm is slower. Furthermore, qualitative analysis of the in-person study interviews reveals that the waiting was not time wasted, but was often used to reﬂect on, and think deliberately about the task and the estimation process of themselves and the algorithm, and to compare and reevaluate the two processes. Based on these ﬁndings, I outline design implications for future algorithmic systems. 2.6% topic match

2.6%

39.5

2007

[165] In Google We Trust: Users' Decisions on Rank, Position, and Relevance Bing Pan, ..., and Laura A. Granka J. Comput. Mediat. Commun. 2007 - 688 citations - Show abstract - Cite - PDF 2.6% topic match

2.5%

0.2

2016

[166] Using interaction data for improving the offline and online evaluation of search engines Evgeny Kharitonov Journal Not Provided 2016 - 2 citations - Show abstract - Cite Abstract: This thesis investigates how web search evaluation can be improved using historical interaction data. Modern search engines combine offline and online evaluation approaches in a sequence of steps that a tested change needs to pass through to be accepted as an improvement and subsequently deployed. We refer to such a sequence of steps as an evaluation pipeline. In this thesis, we consider the evaluation pipeline to contain three sequential steps: an offline evaluation step, an online evaluation scheduling step, and an online evaluation step. In this thesis we show that historical user interaction data can aid in improving the accuracy or efficiency of each of the steps of the web search evaluation pipeline. As a result of these improvements, the overall efficiency of the entire evaluation pipeline is increased. Firstly, we investigate how user interaction data can be used to build accurate offline evaluation methods for query auto-completion mechanisms. We propose a family of offline evaluation metrics for query auto-completion that represents the effort the user has to spend in order to submit their query. The parameters of our proposed metrics are trained against a set of user interactions recorded in the search engine’s query logs. From our experimental study, we observe that our proposed metrics are significantly more correlated with an online user satisfaction indicator than the metrics proposed in the existing literature. Hence, fewer changes will pass the offline evaluation step to be rejected after the online evaluation step. As a result, this would allow us to achieve a higher efficiency of the entire evaluation pipeline. Secondly, we state the problem of the optimised scheduling of online experiments. We tackle this problem by considering a greedy scheduler that prioritises the evaluation queue according to the predicted likelihood of success of a particular experiment. This predictor is trained on a set of online experiments, and uses a diverse set of features to represent an online experiment. Our study demonstrates that a higher number of successful experiments per unit of time can be achieved by deploying such a scheduler on the second step of the evaluation pipeline. Consequently, we argue that the efficiency of the evaluation pipeline can be increased. Next, to improve the efficiency of the online evaluation step, we propose the Generalised Team Draft interleaving framework. Generalised Team Draft considers both the interleaving policy (how often a particular combination of results is shown) and click scoring (how important each click is) as parameters in a data-driven optimisation of the interleaving sensitivity. Further, Generalised Team Draft is applicable beyond domains with a list-based representation of results, i.e. in domains with a grid-based representation, such as image search. Our study using datasets of interleaving experiments performed both in document and image search domains demonstrates that Generalised Team Draft achieves the highest sensitivity. A higher sensitivity indicates that the interleaving experiments can be deployed for a shorter period of time or use a smaller sample of users. Importantly, Generalised Team Draft optimises the interleaving parameters w.r.t. historical interaction data recorded in the interleaving experiments. Finally, we propose to apply the sequential testing methods to reduce the mean deployment time for the interleaving experiments. We adapt two sequential tests for the interleaving experimentation. We demonstrate that one can achieve a significant decrease in experiment duration by using such sequential testing methods. The highest efficiency is achieved by the sequential tests that adjust their stopping thresholds using historical interaction data recorded in diagnostic experiments. Our further experimental study demonstrates that cumulative gains in the online experimentation efficiency can be achieved by combining the interleaving sensitivity optimisation approaches, including Generalised Team Draft, and the sequential testing approaches. Overall, the central contributions of this thesis are the proposed approaches to improve the accuracy or efficiency of the steps of the evaluation pipeline: the offline evaluation frameworks for the query auto-completion, an approach for the optimised scheduling of online experiments, a general framework for the efficient online interleaving evaluation, and a sequential testing approach for the online search evaluation. The experiments in this thesis are based on massive real-life datasets obtained from Yandex, a leading commercial search engine. These experiments demonstrate the potential of the proposed approaches to improve the efficiency of the evaluation pipeline. 2.5% topic match

2.5%

0.2

2012

[167] Relevance Ranking for Predicting Web Search Results Pedro Teixeira Journal Not Provided 2012 - 2 citations - Show abstract - Cite 2.5% topic match

2.5%

1.0

2014

[168] Characterizing multi-click search behavior and the risks and opportunities of changing results during use Chia-Jung Lee, ..., and S. D. L. Chica Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval 2014 - 10 citations - Show abstract - Cite 2.5% topic match

2.5%

8.3

2019

[169] Let's measure run time! Extending the IR replicability infrastructure to include performance aspects Sebastian Hofstätter and A. Hanbury Journal Not Provided 2019 - 43 citations - Show abstract - Cite - PDF 2.5% topic match

2.5%

1.3

2013

[170] Hybrid Query Scheduling for a Replicated Search Engine Ana Freire, ..., and Fidel Cacheda European Conference on Information Retrieval 2013 - 15 citations - Show abstract - Cite 2.5% topic match

2.5%

1.4

2007

[171] The impact of time constraints on Internet and Web use Debra J. Slone J. Assoc. Inf. Sci. Technol. 2007 - 24 citations - Show abstract - Cite 2.5% topic match

2.4%

3.0

2019

[172] Analyzing Web Search Behavior for Software Engineering Tasks N. Rao, ..., and Nachiappan Nagappan 2020 IEEE International Conference on Big Data (Big Data) 2019 - 14 citations - Show abstract - Cite - PDF 2.4% topic match

2.4%

2.5

2024

[173] Generative Information Retrieval Evaluation Marwah Alaofi, ..., and Mark Sanderson ArXiv 2024 - 1 citations - Show abstract - Cite - PDF 2.4% topic match

2.4%

140.2

2013

[174] The tail at scale J. Dean and L. Barroso Commun. ACM 2013 - 1626 citations - Show abstract - Cite 2.4% topic match

2.4%

7.8

2012

[175] Effects of search interface and Internet-specific epistemic beliefs on source evaluations during Web search for medical information: an eye-tracking study Yvonne Kammerer and Peter Gerjets Behaviour & Information Technology 2012 - 99 citations - Show abstract - Cite 2.4% topic match

2.3%

5.5

2014

[176] Cross-Device Search George D. Montañez, ..., and X. Huang Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management 2014 - 54 citations - Show abstract - Cite 2.3% topic match

2.3%

1.0

2017

[177] Household bandwidth and the ‘need for speed’: Evaluating the impact of active queue management for home internet traffic Jenny Kennedy, ..., and Julian Thomas Australian Journal of Telecommunications and the Digital Economy 2017 - 7 citations - Show abstract - Cite 2.3% topic match

2.3%

5.2

2010

[178] Predicting task difficulty for different task types Jingjing Liu, ..., and N. Belkin ASIS&T Annual Meeting 2010 - 72 citations - Show abstract - Cite - PDF 2.3% topic match

2.2%

0.9

2011

[179] A Specialized Search Assistant for Learning Objects Cecilia Curlango-Rosas, ..., and Gabriel López-Morteo ACM Trans. Web 2011 - 11 citations - Show abstract - Cite 2.2% topic match

2.2%

3.3

1998

[180] Interference from short-term memory processing on encoding and reproducing brief durations C. Fortin and R. Rousseau Psychological Research 1998 - 88 citations - Show abstract - Cite 2.2% topic match

2.2%

1.0

2018

[181] Efficient Energy Management in Distributed Web Search Matteo Catena, ..., and N. Tonellotto Proceedings of the 27th ACM International Conference on Information and Knowledge Management 2018 - 6 citations - Show abstract - Cite - PDF 2.2% topic match

2.2%

74.9

2009

[182] Information Foraging P. Pirolli https://doi.org/10.1007/978-0-387-39940-9_205 2009 - 1174 citations - Show abstract - Cite 2.2% topic match

2.1%

3.2

2016

[183] What Affects Word Changes in Query Reformulation During a Task-based Search Session? Jiepu Jiang and Chaoqun Ni Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval 2016 - 27 citations - Show abstract - Cite - PDF 2.1% topic match

2.1%

1.4

2018

[184] Exploring People's Attitudes and Behaviors Toward Careful Information Seeking in Web Search Takehiro Yamamoto, ..., and Sumio Fujita Proceedings of the 27th ACM International Conference on Information and Knowledge Management 2018 - 8 citations - Show abstract - Cite 2.1% topic match

2.1%

6.4

2008

[185] User adaptation: good results from poor systems Catherine L. Smith and P. Kantor Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2008 - 104 citations - Show abstract - Cite 2.1% topic match

2.1%

9.8

2015

[186] CA-DAG: Modeling Communication-Aware Applications for Scheduling in Cloud Computing D. Kliazovich, ..., and Albert Y. Zomaya Journal of Grid Computing 2015 - 91 citations - Show abstract - Cite - PDF 2.1% topic match

2.1%

0.4

2003

[187] An experimental study of Web switching behavior James R. Otto, ..., and William P. Wagner Human systems management 2003 - 8 citations - Show abstract - Cite 2.1% topic match

2.1%

9.6

2003

[188] Predictive caching and prefetching of query results in search engines R. Lempel and S. Moran The Web Conference 2003 - 205 citations - Show abstract - Cite - PDF 2.1% topic match

2.1%

1.9

2017

[189] Comparative experimental analysis of the quality-of-service and energy-efficiency of VMs and containers' consolidation for cloud applications Ismael Cuadrado-Cordero, ..., and Jean-Marc Menaud 2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM) 2017 - 13 citations - Show abstract - Cite - PDF 2.1% topic match

2.0%

7.0

2016

[190] Quality versus efficiency in document scoring with learning-to-rank models Gabriele Capannini, ..., and N. Tonellotto Inf. Process. Manag. 2016 - 55 citations - Show abstract - Cite - PDF 2.0% topic match

2.0%

3.0

2019

[191] How Time Constraints in a Creativity Support Tool Affect the Creative Writing Experience M. M. Biskjaer, ..., and P. Dalsgaard Proceedings of the 31st European Conference on Cognitive Ergonomics 2019 - 15 citations - Show abstract - Cite 2.0% topic match

2.0%

84.1

2002

[192] Web Site Usability, Design, and Performance Metrics J. Palmer Inf. Syst. Res. 2002 - 1872 citations - Show abstract - Cite 2.0% topic match

2.0%

74.7

2005

[193] Accurately interpreting clickthrough data as implicit feedback T. Joachims, ..., and Geri Gay Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2005 - 1425 citations - Show abstract - Cite - PDF 2.0% topic match

2.0%

0.2

2014

[194] Walk like Internet Giants: Konsequenzen für Forschung und Lehre in der Wirtschaftsinformatik W. Brenner, ..., and Lothar Wieske https://doi.org/10.1007/978-3-642-54411-8_2 2014 - 2 citations - Show abstract - Cite 2.0% topic match

2.0%

5.5

2012

[195] Time drives interaction: simulating sessions in diverse searching environments F. Baskaya, ..., and K. Järvelin Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2012 - 66 citations - Show abstract - Cite 2.0% topic match

1.9%

0.0

2024

[196] The impact of clock timing on VDT visual search performance under time constraint Jiabin Hu, ..., and Jingkang He Frontiers in Psychology 2024 - 0 citations - Show abstract - Cite Abstract: Introduction Conducting Visual Display Terminal (VDT) visual search tasks under time constraint has broad applications in fields such as security checks, medical diagnostics, and rescue operations. While excessive time pressure can impair performance, moderate time pressure can motivate individuals to complete tasks and increase productivity. Investigating the positive impact of time pressure on visual search tasks has become a crucial area of study. Clock timing plays a vital role in the visual interface, influencing the perception of time pressure and impacting visual search performance. However, existing research has paid little attention to the induction of time pressure and the impact of clock timing in VDT visual interfaces on visual search performance. Hence, the objective of this study is to investigate the impact of clock timing on VDT visual search performance under time constraint. Methods The content of the experimental tasks was determined through a pilot experiment. The formal experiment was conducted in two phases over six sessions. Participants were tasked with locating the letter “E” embedded within the distractor letter “F,” displayed with a clock area above the interface. The first phase of experiments included conditions of no clock, 4-min clock timing, and 4-min countdown clock timing. In the second phase of the experiment, the clock display method was a countdown clock, with three experiments conducted featuring long time, medium time, and short time. Search speed and accuracy were used as primary performance evaluation metrics to examine the impact of clock timing methods and duration on visual search performance. Twenty-one undergraduate students participated in the formal experiment. Results In the first phase of experiments, participants demonstrated significantly faster reaction times (RTs) in tasks where a clock display was present compared to tasks without (ANOVA, F(2, 60) = 4.588, P = 0.014). However, there were no significant differences in accuracy rates across different timing conditions (ANOVA, F(2, 60) = 0.146, P = 0.865), and no significant correlation between RTs and accuracy was found (Kendall’s R = 0.11, P = 0.914). During the second phase, RTs decreased significantly as time constraints became more stringent (ANOVA, F(2, 60) = 7.564, P < 0.05). Conversely, accuracy rates decreased significantly under shorter time constraints (ANOVA, F(2, 60) = 4.315, P < 0.05), with a negative correlation observed between RTs and accuracy (Kendall’s R = 0.220, P < 0.01). Discussion Compared to conditions without clock displays, having clock displays significantly improved the speed of the visual search task, although the difference in accuracy was not statistically significant. In the context of shorter clock countdown limits, Shorter timing constraints resulted in faster search speeds but also led to reduced accuracy and increased fatigue. Overall, a correlation exists between search speed and accuracy in visual tasks, where higher speed often correlates with lower accuracy. These findings provide valuable insights into clock timing design for visual search interfaces under time pressure. 1.9% topic match

1.9%

1.9

2014

[197] A self-adapting latency/power tradeoff model for replicated search engines Ana Freire, ..., and Fidel Cacheda Proceedings of the 7th ACM international conference on Web search and data mining 2014 - 20 citations - Show abstract - Cite - PDF 1.9% topic match

1.9%

1.9

2014

[198] Explorer Querying Big Graphs Within Bounded Resources W. Fan, ..., and Yinghui Wu Journal Not Provided 2014 - 20 citations - Show abstract - Cite 1.9% topic match

1.8%

12.0

2014

[199] Searching, browsing, and clicking in a search session: changes in user behavior by task and over time Jiepu Jiang, ..., and J. Allan Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval 2014 - 122 citations - Show abstract - Cite 1.8% topic match

1.8%

3.4

2021

[200] Towards Representative Web Performance Measurements with Google Lighthouse Tjaša Heričko, ..., and Saša Brdnik Proceedings of the 2021 7th Student Computer Science Research Conference (StuCoSReC) 2021 - 10 citations - Show abstract - Cite 1.8% topic match

1.8%

0.2

2012

[201] A system for flexible parallel execution David I. August and A. Raman Journal Not Provided 2012 - 3 citations - Show abstract - Cite 1.8% topic match

1.8%

12.9

2007

[202] The impact of caching on search engines Ricardo Baeza-Yates, ..., and F. Silvestri Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007 - 221 citations - Show abstract - Cite - PDF 1.8% topic match

1.8%

3.1

2022

[203] Investigating the Relationship between In‐Situ User Expectations and Web Search Behavior Ben Wang and Jiqun Liu Proceedings of the Association for Information Science and Technology 2022 - 6 citations - Show abstract - Cite 1.8% topic match

1.7%

4.4

2019

[204] Challenges in Search on Streaming Services: Netflix Case Study Sudarshan Lamkhede and Sudeep Das Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval 2019 - 24 citations - Show abstract - Cite - PDF 1.7% topic match

1.7%

11.4

2005

[205] How users assess Web pages for information seeking A. Tombros, ..., and J. Jose J. Assoc. Inf. Sci. Technol. 2005 - 223 citations - Show abstract - Cite - PDF 1.7% topic match

1.7%

5.7

2016

[206] Online Experimentation Diagnosis and Troubleshooting Beyond AA Validation Zhenyu Zhao, ..., and M. Stone 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA) 2016 - 45 citations - Show abstract - Cite 1.7% topic match

1.7%

0.6

2016

[207] Scalability and Efficiency Challenges in Large-Scale Web Search Engines B. B. Cambazoglu and R. Baeza-Yates Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval 2016 - 5 citations - Show abstract - Cite 1.7% topic match

1.7%

0.3

1990

[208] Perceived costs and benefits as determinants of user behaviour: an experiment with matchmaking Dov Te’eni Behaviour & Information Technology 1990 - 9 citations - Show abstract - Cite 1.7% topic match

1.6%

2.5

2016

[209] Experience Report: Detecting Poor-Responsive UI in Android Applications Yu Kang, ..., and Michael R. Lyu 2016 IEEE 27th International Symposium on Software Reliability Engineering (ISSRE) 2016 - 20 citations - Show abstract - Cite 1.6% topic match

1.6%

1.1

2019

[210] Exploring User Behavior in Email Re-Finding Tasks J. Mackenzie, ..., and Milad Shokouhi The World Wide Web Conference 2019 - 6 citations - Show abstract - Cite 1.6% topic match

1.6%

8.9

1984

[211] Response time and display rate in human performance with computers B. Shneiderman ACM Comput. Surv. 1984 - 356 citations - Show abstract - Cite - PDF 1.6% topic match

1.5%

9.7

2008

[212] A probability ranking principle for interactive information retrieval N. Fuhr Information Retrieval 2008 - 157 citations - Show abstract - Cite 1.5% topic match

1.5%

1.1

2019

[213] Loading… loading… The influence of download time on information search Alyssa C. Smith, ..., and D. Smilek PLoS ONE 2019 - 5 citations - Show abstract - Cite - PDF 1.5% topic match

1.5%

0.0

2014

[214] Query Scheduling Techniques and Power/Latency Trade-off Model for Large-Scale Search Engines Ana Maŕıa Freire Veiga Journal Not Provided 2014 - 0 citations - Show abstract - Cite 1.5% topic match

1.5%

1.9

2023

[215] A Systematic Review of Cost, Effort, and Load Research in Information Search and Retrieval, 1972–2020 Molly McGregor, ..., and Martin Halvey ACM Transactions on Information Systems 2023 - 3 citations - Show abstract - Cite - PDF 1.5% topic match

1.5%

2.6

2023

[216] Don't Forget the User: It's Time to Rethink Network Measurements Aryan Taneja, ..., and Ross Cutler Proceedings of the 22nd ACM Workshop on Hot Topics in Networks 2023 - 2 citations - Show abstract - Cite 1.5% topic match

1.5%

0.0

2017

[217] Improving Retrieval Effectiveness for Temporal-Constrained Top-K Query Processing Hao Wu, ..., and Hui Fang Asia Information Retrieval Symposium 2017 - 0 citations - Show abstract - Cite 1.5% topic match

1.5%

3.1

2015

[218] Session Search by Direct Policy Learning Jiyun Luo, ..., and G. Yang Proceedings of the 2015 International Conference on The Theory of Information Retrieval 2015 - 28 citations - Show abstract - Cite 1.5% topic match

1.5%

3.2

2017

[219] Energy-Efficient Query Processing in Web Search Engines Matteo Catena and N. Tonellotto IEEE Transactions on Knowledge and Data Engineering 2017 - 23 citations - Show abstract - Cite Abstract: Web search engines are composed by thousands of query processing nodes, i.e., servers dedicated to process user queries. Such many servers consume a significant amount of energy, mostly accountable to their CPUs, but they are necessary to ensure low latencies, since users expect sub-second response times (e.g., 500 ms). However, users can hardly notice response times that are faster than their expectations. Hence, we propose the Predictive Energy Saving Online Scheduling Algorithm (<inline-formula><tex-math notation="LaTeX">$\sf{PESOS}$</tex-math> <alternatives><inline-graphic xlink:href="catena-ieq1-2681279.gif"/></alternatives></inline-formula>) to select the most appropriate CPU frequency to process a query on a per-core basis. <inline-formula><tex-math notation="LaTeX"> $\sf{PESOS}$</tex-math><alternatives><inline-graphic xlink:href="catena-ieq2-2681279.gif"/></alternatives> </inline-formula> aims at process queries by their deadlines, and leverage high-level scheduling information to reduce the CPU energy consumption of a query processing node. <inline-formula><tex-math notation="LaTeX"> $\sf{PESOS}$</tex-math><alternatives><inline-graphic xlink:href="catena-ieq3-2681279.gif"/></alternatives> </inline-formula> bases its decision on query efficiency predictors, estimating the processing volume and processing time of a query. We experimentally evaluate <inline-formula><tex-math notation="LaTeX">$\sf{PESOS}$ </tex-math><alternatives><inline-graphic xlink:href="catena-ieq4-2681279.gif"/></alternatives></inline-formula> upon the TREC ClueWeb09B collection and the MSN2006 query log. Results show that <inline-formula><tex-math notation="LaTeX"> $\sf{PESOS}$</tex-math><alternatives><inline-graphic xlink:href="catena-ieq5-2681279.gif"/></alternatives> </inline-formula> can reduce the CPU energy consumption of a query processing node up to <inline-formula> <tex-math notation="LaTeX">${\sim}$</tex-math><alternatives> <inline-graphic xlink:href="catena-ieq6-2681279.gif"/></alternatives></inline-formula>48 percent compared to a system running at maximum CPU core frequency. <inline-formula><tex-math notation="LaTeX">$\sf{PESOS}$</tex-math> <alternatives><inline-graphic xlink:href="catena-ieq7-2681279.gif"/></alternatives></inline-formula> outperforms also the best state-of-the-art competitor with a <inline-formula><tex-math notation="LaTeX">${\sim}$</tex-math> <alternatives><inline-graphic xlink:href="catena-ieq8-2681279.gif"/></alternatives></inline-formula>20 percent energy saving, while the competitor requires a fine parameter tuning and it may incurs in uncontrollable latency violations. 1.5% topic match

1.5%

16.6

2020

[220] Interpretable & Time-Budget-Constrained Contextualization for Re-Ranking Sebastian Hofstätter, ..., and A. Hanbury European Conference on Artificial Intelligence 2020 - 76 citations - Show abstract - Cite - PDF 1.5% topic match

1.5%

6.5

2014

[221] Understanding Within-Content Engagement through Pattern Analysis of Mouse Gestures Ioannis Arapakis, ..., and G. Valkanas Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management 2014 - 64 citations - Show abstract - Cite - PDF 1.5% topic match

1.5%

0.7

2012

[222] Human question answering performance using an interactive document retrieval system Mark D. Smucker, ..., and B. Dachev International Conference on Information Interaction in Context 2012 - 8 citations - Show abstract - Cite 1.5% topic match

1.4%

16.0

2000

[223] Integrating user-perceived quality into Web server design N. Bhatti, ..., and A. Kuchinsky Comput. Networks 2000 - 388 citations - Show abstract - Cite - PDF 1.4% topic match

1.4%

1.6

2021

[224] Microtask Detection Ryen W. White, ..., and S. Jauhar ACM Transactions on Information Systems (TOIS) 2021 - 6 citations - Show abstract - Cite 1.4% topic match

1.4%

0.0

2013

[225] Improving web user experience with caching user interface A. Opalinski https://doi.org/10.21936/SI2013_V34.N2B.62 2013 - 0 citations - Show abstract - Cite 1.4% topic match

1.4%

0.4

2009

[226] Making the road by searching - A search engine based on Swarm Information Foraging Daniel Gayo-Avello and David J. Brenes ArXiv 2009 - 6 citations - Show abstract - Cite - PDF 1.4% topic match

1.4%

1.0

2014

[227] User-controlled resource management in federated clouds Marc Mosch, ..., and A. Schill Journal of Cloud Computing 2014 - 10 citations - Show abstract - Cite - PDF 1.4% topic match

1.4%

0.7

2017

[228] The Tetris Model of Resolving Information Needs within the Information Seeking Process Max L. Wilson Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval 2017 - 5 citations - Show abstract - Cite - PDF 1.4% topic match

1.4%

0.1

2010

[229] Perceived and Actual Web Page Loading Delay: What Difference Do Predictive Feedback Information (PFI) Cues Make? Mohamed Louadi and I. B. Ali J. Inf. Technol. Res. 2010 - 2 citations - Show abstract - Cite 1.4% topic match

1.4%

9.1

2016

[230] UQV100: A Test Collection with Query Variability P. Bailey, ..., and Paul Thomas Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval 2016 - 74 citations - Show abstract - Cite 1.4% topic match

1.3%

0.6

2009

[231] Towards Timed Predictions of Human Performance for Interactive Information Retrieval Evaluation Mark D. Smucker Journal Not Provided 2009 - 9 citations - Show abstract - Cite 1.3% topic match

1.3%

5.7

2015

[233] Delayed-Dynamic-Selective (DDS) Prediction for Reducing Extreme Tail Latency in Web Search Saehoon Kim, ..., and Seungjin Choi Proceedings of the Eighth ACM International Conference on Web Search and Data Mining 2015 - 55 citations - Show abstract - Cite 1.3% topic match

1.3%

2.4

2021

[234] A Method to Manipulate Subjective Time by using Tactile Stimuli of Wearable Device Kiichi Shirai, ..., and Kazuya Murao Proceedings of the 2021 ACM International Symposium on Wearable Computers 2021 - 7 citations - Show abstract - Cite 1.3% topic match

1.3%

3.1

2014

[235] Time-critical search Nina Mishra, ..., and E. Horvitz Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval 2014 - 32 citations - Show abstract - Cite 1.3% topic match

1.2%

3.0

2002

[236] Web searching: A process-oriented experimental study of three interactive search paradigms S. Dennis, ..., and R. McArthur J. Assoc. Inf. Sci. Technol. 2002 - 68 citations - Show abstract - Cite 1.2% topic match

1.2%

0.0

2024

[237] Key Flow First Prioritized Flow Scheduling Strategy in Multi-Tenant Data Centers Xudong Tao, ..., and Rui Xu IEEE Transactions on Network and Service Management 2024 - 0 citations - Show abstract - Cite 1.2% topic match

1.2%

0.0

2020

[238] Continuous Click Behavior in Academic Search Environment Zhu Liang, ..., and Si Shen Journal Not Provided 2020 - 0 citations - Show abstract - Cite 1.2% topic match

1.2%

16.1

2015

[239] Development and Evaluation of Search Tasks for IIR Experiments using a Cognitive Complexity Framework D. Kelly, ..., and Wan-Ching Wu Proceedings of the 2015 International Conference on The Theory of Information Retrieval 2015 - 144 citations - Show abstract - Cite 1.2% topic match

1.2%

5.2

2017

[240] A Study of Snippet Length and Informativeness: Behaviour, Performance and User Experience David Maxwell, ..., and Yashar Moshfeghi Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval 2017 - 37 citations - Show abstract - Cite - PDF 1.2% topic match

1.2%

1.4

2016

[241] Correlating QoE and Technical Parameters of an SAP System in an Enterprise Environment Kathrin Borchert, ..., and D. Mocanu 2016 28th International Teletraffic Congress (ITC 28) 2016 - 11 citations - Show abstract - Cite 1.2% topic match

1.2%

6.1

2019

[242] Investigating Cognitive Effects in Session-level Search User Satisfaction Mengyang Liu, ..., and Shaoping Ma Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2019 - 31 citations - Show abstract - Cite 1.2% topic match

1.2%

2.0

2014

[243] Slow search J. Teevan, ..., and S. Dumais Commun. ACM 2014 - 20 citations - Show abstract - Cite 1.2% topic match

1.2%

2.0

2018

[244] Efficient and Effective Query Expansion for Web Search C. Lucchese, ..., and Rossano Venturini Proceedings of the 27th ACM International Conference on Information and Knowledge Management 2018 - 12 citations - Show abstract - Cite - PDF 1.2% topic match

1.1%

None

[245] Journal of the Association for Information Systems Dina Koutsikouri, ..., and Daniel Rudmark Journal Not Provided None - 359 citations - Show abstract - Cite 1.1% topic match

1.1%

2.0

2006

[246] A Comparative Study of the Effectiveness of Search Result Presentation on the Web Hideo Joho and J. Jose European Conference on Information Retrieval 2006 - 36 citations - Show abstract - Cite - PDF 1.1% topic match

1.1%

3.3

2010

[247] How the interface design influences users' spontaneous trustworthiness evaluations of web search results: comparing a list and a grid interface Yvonne Kammerer and Peter Gerjets Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications 2010 - 48 citations - Show abstract - Cite 1.1% topic match

1.1%

0.6

2013

[248] Fading Away: Dilution and User Behaviour Paul Thomas, ..., and Alistair Moffat European Workshop on Human-Computer Interaction and Information Retrieval 2013 - 7 citations - Show abstract - Cite 1.1% topic match

1.1%

0.7

2017

[249] Tianji: Implementation of an Efficient Tracking Engine in the Mobile Internet Era Jin-Yuan Chen, ..., and Cong-Zhi Zhao IEEE Access 2017 - 5 citations - Show abstract - Cite 1.1% topic match

1.1%

10.1

2011

[250] Inferring and using location metadata to personalize web search Paul N. Bennett, ..., and Emine Yilmaz Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval 2011 - 132 citations - Show abstract - Cite 1.1% topic match

1.1%

3.1

2018

[251] Towards Designing Better Session Search Evaluation Metrics Mengyang Liu, ..., and Shaoping Ma The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval 2018 - 19 citations - Show abstract - Cite 1.1% topic match

1.1%

5.3

2023

[252] Forget Me Now: Fast and Exact Unlearning in Neighborhood-based Recommendation Sebastian Schelter, ..., and M. de Rijke Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval 2023 - 6 citations - Show abstract - Cite - PDF 1.1% topic match

1.1%

0.0

2016

[253] Improving efficiency and flexibility of information retrieval systems H. Wu Journal Not Provided 2016 - 0 citations - Show abstract - Cite 1.1% topic match

1.1%

0.3

2021

[254] Key issues for a manufacturing data query system based on graph Lise Kim, ..., and Victor Fau International Journal on Interactive Design and Manufacturing (IJIDeM) 2021 - 1 citations - Show abstract - Cite - PDF 1.1% topic match

1.1%

16.0

2018

[255] μ Suite: A Benchmark Suite for Microservices Akshitha Sriraman and T. Wenisch 2018 IEEE International Symposium on Workload Characterization (IISWC) 2018 - 96 citations - Show abstract - Cite 1.1% topic match

1.0%

1.1

2017

[256] Predicting Online Shopping Search Satisfaction and User Behaviors with Electrodermal Activity Yingying Wu, ..., and Wenwu Ou Proceedings of the 26th International Conference on World Wide Web Companion 2017 - 8 citations - Show abstract - Cite 1.0% topic match

1.0%

0.3

2014

[257] Algorithms and Techniques for Proactive Search Christopher Shaun Wagner, ..., and A. Hurson J. Inf. Process. 2014 - 3 citations - Show abstract - Cite - PDF 1.0% topic match

1.0%

4.0

1993

[258] Improving user satisfaction: the questionnaire for user interaction satisfaction version 5 Ben D. Harper and K. Norman Journal Not Provided 1993 - 126 citations - Show abstract - Cite 1.0% topic match

1.0%

2.3

1982

[259] A cost-benefit mechanism for selecting problem-solving strategies: Some extensions and empirical tests James F. Smith, ..., and L. Beach Organizational Behavior and Human Performance 1982 - 97 citations - Show abstract - Cite 1.0% topic match

1.0%

15.0

1999

[260] User interface directions for the Web J. Nielsen Commun. ACM 1999 - 384 citations - Show abstract - Cite - PDF 1.0% topic match

1.0%

0.0

2019

[261] Evaluating Variable-Length Multiple-Option Lists in Chatbots and Mobile Search Pepa Atanasova, ..., and F. Sebastiani Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval 2019 - 0 citations - Show abstract - Cite - PDF 1.0% topic match

1.0%

2.6

1983

[262] System response time operator productivity, and job satisfaction Raymond E. Barber and H. Lucas New York University Stern School of Business Research Paper Series 1983 - 110 citations - Show abstract - Cite - PDF 1.0% topic match

1.0%

2.7

1991

[263] How Long Should a Customer Wait for Service M. M. Davis Decision Sciences 1991 - 92 citations - Show abstract - Cite 1.0% topic match

1.0%

0.8

2015

[264] Identifying Web Performance Degradations through Synthetic and Real-User Monitoring Jürgen Cito, ..., and S. Dustdar J. Web Eng. 2015 - 7 citations - Show abstract - Cite 1.0% topic match

1.0%

14.8

1988

[265] Time and Organizations Allen C. Bluedorn and Robert B. Denhardt Journal of Management 1988 - 536 citations - Show abstract - Cite 1.0% topic match

1.0%

8.2

2014

[266] Predictive parallelization: taming tail latencies in web search Myeongjae Jeon, ..., and S. Rixner Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval 2014 - 83 citations - Show abstract - Cite Abstract: Web search engines are optimized to reduce the high-percentile response time to consistently provide fast responses to almost all user queries. This is a challenging task because the query workload exhibits large variability, consisting of many short-running queries and a few long-running queries that significantly impact the high-percentile response time. With modern multicore servers, parallelizing the processing of an individual query is a promising solution to reduce query execution time, but it gives limited benefits compared to sequential execution since most queries see little or no speedup when parallelized. The root of this problem is that short-running queries, which dominate the workload, do not benefit from parallelization. They incur a large parallelization overhead, taking scarce resources from long-running queries. On the other hand, parallelization substantially reduces the execution time of long-running queries with low overhead and high parallelization efficiency. Motivated by these observations, we propose a predictive parallelization framework with two parts: (1) predicting long-running queries, and (2) selectively parallelizing them. For the first part, prediction should be accurate and efficient. For accuracy, we study a comprehensive feature set covering both term features (reflecting dynamic pruning efficiency) and query features (reflecting query complexity). For efficiency, to keep overhead low, we avoid expensive features that have excessive requirements such as large memory footprints. For the second part, we use the predicted query execution time to parallelize long-running queries and process short-running queries sequentially. We implement and evaluate the predictive parallelization framework in Microsoft Bing search. Our measurements show that under moderate to heavy load, the predictive strategy reduces the 99th-percentile response time by 50% (from 200 ms to 100 ms) compared with prior approaches that parallelize all queries. 1.0% topic match

0.9%

0.0

2015

[267] Short Visit Report – Modeling and Evaluating User Interaction in IR Tuan V. Tran Journal Not Provided 2015 - 0 citations - Show abstract - Cite 0.9% topic match

0.9%

2.4

2021

[268] Reducing Risk in Digital Self-Control Tools: Design Patterns and Prototype R. Schwartz, ..., and P. Apostolellis Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems 2021 - 8 citations - Show abstract - Cite 0.9% topic match

0.9%

0.0

2013

[269] Directly " Evaluating " the " Cognitive " Impact " of " Search " User " Interfaces : " a " TwoF Pronged " Approach " with " fNIRS Alistair Moffat, ..., and Stefan Haun Journal Not Provided 2013 - 0 citations - Show abstract - Cite 0.9% topic match

0.9%

0.5

2018

[271] Online Personalization in Exploratory Search J. Pyykkö Journal Not Provided 2018 - 3 citations - Show abstract - Cite 0.9% topic match

0.9%

8.9

2011

[272] The economics in interactive information retrieval L. Azzopardi Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval 2011 - 117 citations - Show abstract - Cite - PDF 0.9% topic match

0.9%

4.3

2021

[273] LogUI: Contemporary Logging Infrastructure for Web-Based Experiments David Maxwell and C. Hauff European Conference on Information Retrieval 2021 - 16 citations - Show abstract - Cite - PDF 0.9% topic match

0.9%

1.3

2021

[274] Incorporating Widget Positioning in Interaction Models of Search Behaviour Nirmal Roy, ..., and C. Hauff Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval 2021 - 4 citations - Show abstract - Cite - PDF 0.9% topic match

0.8%

6.2

2021

[275] Deconstructing search tasks in interactive information retrieval: A systematic review of task dimensions and predictors Jiqun Liu Inf. Process. Manag. 2021 - 23 citations - Show abstract - Cite 0.8% topic match

0.8%

51.2

2003

[276] Web Search for a Planet: The Google Cluster Architecture L. Barroso, ..., and Urs Hölzle IEEE Micro 2003 - 1101 citations - Show abstract - Cite 0.8% topic match

0.8%

6.0

2014

[277] PARCEL: Proxy Assisted BRowsing in Cellular networks for Energy and Latency reduction A. Sivakumar, ..., and S. Sen Proceedings of the 10th ACM International on Conference on emerging Networking Experiments and Technologies 2014 - 59 citations - Show abstract - Cite 0.8% topic match

0.8%

5.1

2004

[278] Intra-individual information behaviour in daily life Heidi E. Julien and D. Michels Inf. Process. Manag. 2004 - 105 citations - Show abstract - Cite 0.8% topic match

0.8%

1.8

2019

[280] Evaluation of information retrieval systems using structural equation modeling M. Melucci and Adriano Paggiaro Comput. Sci. Rev. 2019 - 10 citations - Show abstract - Cite - PDF 0.8% topic match

0.8%

0.0

2014

[282] ADULT AGE DIFFERENCES IN INFORMATION FORAGING IN INTERACTIVE READING ENVIRONMENTS BY Xiaomei Liu Journal Not Provided 2014 - 0 citations - Show abstract - Cite 0.8% topic match

0.8%

2.6

2018

[283] Reducing Web Latency Through Dynamically Setting TCP Initial Window with Reinforcement Learning Xiaohui Nie, ..., and Jiyang Zhang 2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS) 2018 - 16 citations - Show abstract - Cite 0.8% topic match

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2.4

2006

[284] Modeling Result-List Searching in the World Wide Web: The Role of Relevance Topologies and Trust Bias Mark T. Keane and Maeve O'Brien Journal Not Provided 2006 - 45 citations - Show abstract - Cite Abstract: Modeling Result-List Searching in the World Wide Web: The Role of Relevance Topologies and Trust Bias Maeve O’Brien (maeve.m.obrien@ucd.ie) Mark T. Keane (mark.keane@ucd.ie) Adaptive Information Cluster, University College Dublin, School of Computer Science and Informatics, University College Dublin, Ireland. Abstract There are important cognitive issues surrounding the searching of lists of results returned to search engine queries that could significantly impact system and interface design. In this paper, we focus on result-list search examining two key issues: the influence of relevance topology of the list on first- click behavior, and the question of whether trust-bias occurs in such search. On both issues we advance some empirical and modeling results. These results are discussed in terms of their practical implications for Web designers and practitioners generally. Keywords: search behavior; information predictive user modeling; empirical tests. navigation; Introduction The World Wide Web (WWW; Berners-Lee, T. Cailliau R. Groff J. & Pollermann B.,1992) has presented people with a whole new medium in which to search for information and, arguably, has transformed list-searching from a rather arcane, laboratory phenomenon into a ubiquitous cognitive act. Currently, there are two predominant modes for locating information on the World Wide Web (WWW): browsing and searching. Browsing is the process of viewing pages one at a time and navigating between them sequentially using hyperlinks. Searching refers to the entering of a search query (usually a list of one or more keywords) to a search engine and the subsequent scanning and selection of links from the results returned. Researchers have developed a number of models of Internet browsing (see Brumby & Howes, 2004; Cox & Young, 2004; Miller & Remington, 2005; Pirolli, 2005; Pirolli & Card, 1999; Pirolli & Fu, 2003). Result-list search has received less attention in the Web context, though for decades it has been a mainstay of memory and attention experiments (see Eysenck & Keane, 2000). There are significant issues surrounding how people search result lists within the Web context. In this paper, we focus on two key issues: the significance of the relevance topology of the list, and the issue of trust bias in search engines. On both issues we advance new empirical and modeling results. It has repeatedly been shown that people tend to favor items presented at the top of lists, an effect that has been replicated in the Web context (Joachims, Granka, Pang, Hembrooke, Gay, 2005; Keane, O’Brien & Smyth, in press). Keane et al. (in press), for example, showed, using a simulated Google (Brin & Page, 1998) interface, that when result-lists are systematically reversed in response to user queries, people tend to choose less-relevant results at the beginning of the list over highly-relevant results lower down the list. This bias raises concerns surrounding the search-engines power to route traffic: highly-ranked pages typically benefit from a greater volume of traffic, and this heightened exposure obviously increases the volume of incoming links these top pages receive over time, which in turn increases their ranking prominence and the volume of traffic they receive etc. resulting in a rich-get-richer scenario (Baeza- Yates, Saint-Jean, Castillo, 2002; Cho & Adams, 2003; Cho, Roy, 2004). A key issue surrounding this bias effect is whether it is specifically due to some level of trust in the particular search engine. For example, as people come to trust the fact that Google tend to deliver relevant links in the first three results, people may stop closely assessing results and just lazily click on these first links (c.f., Joachims et al., 2005). An obvious way to check this is to see whether the effects found by Keane et al. (in press) for the simulated Google interface, are also found when the same materials are presented as simple text lists. In their study Keane et al (in press) found that whilst people generally tended to click on top results, there were instances where highly-relevant results lower down the list were clicked. This effect may be due to the different relevance distributions, or topologies, of result-lists. That is, a highly-relevant result proceeding many irrelevant results may stand a greater chance of being chosen over the same highly-relevant result proceeded by other relatively relevant results. In menu searching, Brumby & Howes (2004) have already shown that the extent to which people search through a list interacts with such relevance topologies. But, it is not clear whether such effects extend to search-engine result lists. In this paper, we present an experiment and a model that investigate these two issues. In the experiment we systematically manipulated the relevance topologies of the presented lists, presenting them in either a Google interface or a text-list interface. 0.8% topic match

0.8%

2.3

2016

[285] Affective capitalism of knowing and the society of search engine Isto Huvila Aslib J. Inf. Manag. 2016 - 18 citations - Show abstract - Cite - PDF 0.8% topic match

0.8%

None

[286] Chapter 1 Introduction 1.1 Motivation No author found Journal Not Provided None - 0 citations - Show abstract - Cite Abstract: Introduced a little over a decade ago, the WorldWide Web has transformed much of the world's economy and will continue to do so. It can be compared to the telephone, television, and automobile as a paradigm shift in the way people work, communicate, and play. As the popular interface to what has been called the " information super-highway " , the Web purports to provide instantaneous access to vast quantities of information. However, the perception of time is always relative — access to information on today's Web is rarely instantaneous. While performance continues to improve over time from improvements in bandwidth and device latencies, users continue to desire yet additional speed [KPS + 99]. Likewise, content providers continue to make greater demands on bandwidth as it increases. Good interactive response-time has long been known to be essential for user satisfaction and productivity [DT82, Bra86, Roa98]. This is also true for the Web [RBP98, BBK00]. A widely-cited study from Zona Research [Zon99] provides evidence for the " eight second rule " — in electronic commerce, if a Web site takes more than eight seconds to load, the user is much more likely to become frustrated and leave the site. Thus there is also significant economic incentive for many content providers to provide a responsive Web experience. 1.1.1 Methods to improve Web response times Many factors contribute to a less-than-speedy Web experience, including heterogeneous network connectivity, real-world distances, and congestion in networks or servers due 1 to unexpected demand. As a result, many researchers (often as entrepreneurs) have considered the problem of improving Web response times. Some want to improve performance by achieving bandwidth increases and response time improvement through bigger " pipes " or alternative communication technologies. Others want to use the existing infrastructure more efficiently. Web caching, along with other forms of data dissemination, has been proposed as a technology that helps reduce network usage and server loads and improve typical response times experienced by the user. When successful , pre-loading Web objects into local caches can be used to further reduce web response times [PM96], and even to shift network loads from peak to non-peak periods [MRGM99]. Our interest is in pre-loading interactively, so that by dynamically pre-loading Web objects likely to be of interest into local caches, we may invisibly improve the user experience by improving the response time. To be more precise, let us start with a … 0.8% topic match

0.8%

9.6

2006

[287] When the Wait Isn't So Bad: The Interacting Effects of Website Delay, Familiarity, and Breadth D. Galletta, ..., and P. Polak Inf. Syst. Res. 2006 - 177 citations - Show abstract - Cite 0.8% topic match

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0.0

2022

[288] Reflection on future directions: a systematic review of reported limitations and solutions in interactive information retrieval user studies Tianji Jiang and Jiqun Liu Aslib J. Inf. Manag. 2022 - 0 citations - Show abstract - Cite 0.8% topic match

0.8%

2.2

2013

[289] Network performance: Does it really matter to users and by how much? R. Sitaraman 2013 Fifth International Conference on Communication Systems and Networks (COMSNETS) 2013 - 25 citations - Show abstract - Cite - PDF 0.8% topic match

0.7%

10.8

2021

[290] This Is Not What We Ordered: Exploring Why Biased Search Result Rankings Affect User Attitudes on Debated Topics Tim Draws, ..., and Benjamin Timmermans Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval 2021 - 34 citations - Show abstract - Cite - PDF 0.7% topic match

0.7%

1.3

1999

[291] Improving response time by search pruning in a content-based image retrieval system, using inverted file techniques McG.D. Squire, ..., and Wolfgang Müller Proceedings IEEE Workshop on Content-Based Access of Image and Video Libraries (CBAIVL'99) 1999 - 32 citations - Show abstract - Cite - PDF 0.7% topic match

0.7%

9.9

2006

[292] Time as a context of information seeking Reijo Savolainen Library & Information Science Research 2006 - 184 citations - Show abstract - Cite 0.7% topic match

0.7%

0.0

2015

[293] A web personalization artifact for utility-sensitive review analysis L. Flory Journal Not Provided 2015 - 0 citations - Show abstract - Cite Abstract: A WEB PERSONALIZATION ARTIFACT FOR UTILITY-SENSITIVE REVIEW ANALYSIS By Long Flory, Ph.D. A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Business at Virginia Commonwealth University Virginia Commonwealth University, 2015. Major Director: Dr. Kweku-Muata Osei-Bryson, Professor, Information Systems Online customer reviews are web content voluntarily posted by the users of a product (e.g. camera) or service (e.g. hotel) to express their opinions about the product or service. Online reviews are important resources for businesses and consumers. This dissertation focuses on the important consumer concern of review utility, i.e., the helpfulness or usefulness of online reviews to inform consumer purchase decisions. Review utility concerns consumers since not all online reviews are useful or helpful. And, the quantity of the online reviews of a product/service tends to be very large. Manual assessment of review utility is not only time consuming but also information overloading. To address this issue, review helpfulness research (RHR) has become a very active research stream dedicated to study utility-sensitive review analysis (USRA) techniques for automating review utility assessment. Unfortunately, prior RHR solution is inadequate. RHR researchers call for more suitable USRA approaches. Our current research responds to this urgent call by addressing the research problem: What is an adequate USRA approach? We address this problem by offering novel Design Science (DS) artifacts for personalized USRA (PUSRA). Our proposed solution extends not only RHR research but also web personalization research (WPR), which studies web-based solutions for personalized web provision. We have evaluated the proposed solution by applying three evaluation methods: analytical, descriptive, and experimental. The evaluations corroborate the practical efficacy of our proposed solution. This research contributes what we believe (1) the first DS artifacts to the knowledge body of RHR and WPR, and (2) the first PUSRA contribution to USRA practice. Moreover, we consider our evaluations of the proposed solution the first comprehensive assessment of USRA solutions. In addition, this research contributes to the advancement of decision support research and practice. The proposed solution is a web-based decision support artifact with the capability to substantially improve accurate personalized webpage provision. Also, website designers can apply our research solution to transform their works fundamentally. Such transformation can add substantial value to businesses. 0.7% topic match

0.7%

4.3

1989

[294] Consumers' Reactions to Waiting: When Delays Affect the Perception of Service Quality Laurette Dubé-Rioux and Bernd H. Schmitt ACR North American Advances 1989 - 155 citations - Show abstract - Cite 0.7% topic match

0.7%

0.0

2016

[295] A Study on Fine-Grained User Behavior Analysis in Web Search Kazutoshi Umemoto https://doi.org/10.14989/DOCTOR.K19852 2016 - 0 citations - Show abstract - Cite Abstract: Web search engines are now used by people with diverse search intents for various purposes. Some tasks they conduct with the search engines cannot be fulfilled just by issuing a single search query or browsing a single document. There are several characteristics common to such complex search tasks. The first two are related to search intents: (1) even if the same query is issued to a search engine, the desired information may differ among searchers, since the search intents behind the query depend on their search contexts; and (2) searchers’ intents can also shift from one to another during a series of their searches on a particular topic. The remaining two concern search outcomes: (3) as complex tasks require searchers to collect more than one relevant document, browsing a single relevant document does not necessarily indicate the success of their search sessions; and (4) this requirement also makes it difficult for searchers to decide when to stop searching. This thesis aims to establish methodologies for understanding diverse intents of searchers and for appreciating their search outcomes in order to help searchers complete complex tasks efficiently and effectively. Our key idea for achieving this aim is analyzing fine-grained user behavior data, where we use the phrase “user behavior” in a broader sense so that it can include search interaction data between searchers and search systems. More specifically, we address the following four research topics in this thesis: 1. Estimating Attractive Terms from Gazing Behavior We address the problem of estimating hidden intents of Web search users from their observable search behavior. To this end, we focus on searchers’ gazing behavior on their browsed Web pages and assume that terms drawing a high degree of the attention of a searcher are likely to be relevant to his/her topical intent. On the basis of this assumption, we propose a method of estimating a set of weighted terms that clarify the searcher’s ambiguous topical intent. Through a laboratory experiment, the proposed method is evaluated from both qualitative and quantitative perspectives. 2. Predicting Query Reformulation from Current Search Behavior 0.7% topic match

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4.3

2016

[296] Agents, Simulated Users and Humans: An Analysis of Performance and Behaviour David Maxwell and L. Azzopardi Proceedings of the 25th ACM International on Conference on Information and Knowledge Management 2016 - 34 citations - Show abstract - Cite - PDF 0.7% topic match

0.7%

1020.8

1988

[297] Development and validation of brief measures of positive and negative affect: the PANAS scales. D. Watson, ..., and A. Tellegen Journal of personality and social psychology 1988 - 37027 citations - Show abstract - Cite 0.7% topic match

0.7%

11.6

1999

[298] Web prefetching between low-bandwidth clients and proxies: potential and performance Li Fan, ..., and Quinn Jacobson Measurement and Modeling of Computer Systems 1999 - 295 citations - Show abstract - Cite - PDF 0.7% topic match

0.7%

2.2

2012

[299] Text selections as implicit relevance feedback Ryen W. White and Georg Buscher Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2012 - 27 citations - Show abstract - Cite - PDF 0.7% topic match

0.7%

2.3

2019

[300] Bridging Gaps: Predicting User and Task Characteristics from Partial User Information M. Mitsui and C. Shah Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval 2019 - 12 citations - Show abstract - Cite - PDF 0.7% topic match

0.7%

1.4

2018

[301] How Consistent is Relevance Feedback in Exploratory Search? A. Medlar and D. Głowacka Proceedings of the 27th ACM International Conference on Information and Knowledge Management 2018 - 8 citations - Show abstract - Cite 0.7% topic match

0.7%

6.1

2013

[302] Robust models of mouse movement on dynamic web search results pages Fernando Diaz, ..., and Daniel J. Liebling Proceedings of the 22nd ACM international conference on Information & Knowledge Management 2013 - 66 citations - Show abstract - Cite 0.7% topic match

0.7%

83.3

2018

[303] A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form H. O'Brien, ..., and Mark Hall Int. J. Hum. Comput. Stud. 2018 - 536 citations - Show abstract - Cite 0.7% topic match

0.6%

9.0

2011

[304] User-click modeling for understanding and predicting search-behavior Yuchen Zhang, ..., and Qiang Yang Knowledge Discovery and Data Mining 2011 - 117 citations - Show abstract - Cite 0.6% topic match

0.6%

0.9

2016

[305] Psychology and Aging Adult Age Differences in Information Foraging in an Interactive Reading Environment Xiaomei Liu, ..., and Elizabeth A. L. Stine-Morrow Journal Not Provided 2016 - 8 citations - Show abstract - Cite 0.6% topic match

0.6%

0.6

2023

[306] CaptainA - A mobile app for practising Finnish pronunciation Nhan Phan, ..., and M. Kurimo Nordic Conference of Computational Linguistics 2023 - 1 citations - Show abstract - Cite - PDF 0.6% topic match

0.6%

0.6

2014

[307] Linked data based exploratory search Nicolas Marie Journal Not Provided 2014 - 6 citations - Show abstract - Cite 0.6% topic match

0.6%

0.2

2014

[308] Exploratory search on mobile devices S. Schmeier Journal Not Provided 2014 - 2 citations - Show abstract - Cite 0.6% topic match

0.6%

12.0

2011

[309] Inferring the QoE of HTTP video streaming from user-viewing activities Ricky K. P. Mok, ..., and R. Chang https://doi.org/10.1145/2018602.2018611 2011 - 156 citations - Show abstract - Cite - PDF 0.6% topic match

0.6%

0.0

2023

[310] Hydrus: Improving Personalized Quality of Experience in Short-form Video Services Zhiyu Yuan, ..., and Xin Miao Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval 2023 - 0 citations - Show abstract - Cite - PDF 0.6% topic match

0.6%

0.0

2022

[311] Distributed Latency Profiling through Critical Path Tracing B. Eaton, ..., and N. Tas Communications of the ACM 2022 - 0 citations - Show abstract - Cite - PDF 0.6% topic match

0.6%

2.6

2016

[312] FluxQuery: An Execution Framework for Highly Interactive Query Workloads Roee Ebenstein, ..., and Arnab Nandi Proceedings of the 2016 International Conference on Management of Data 2016 - 21 citations - Show abstract - Cite - PDF 0.6% topic match

0.6%

6.8

2005

[313] Eye-Tracking Reveals the Personal Styles for Search Result Evaluation A. Aula, ..., and Kari-Jouko Räihä IFIP TC13 International Conference on Human-Computer Interaction 2005 - 129 citations - Show abstract - Cite - PDF 0.6% topic match

0.6%

0.0

2019

[314] An Analysis of Performance and Behaviour David Maxwell and L. Azzopardi Journal Not Provided 2019 - 0 citations - Show abstract - Cite 0.6% topic match

0.6%

1.8

2018

[315] How Much is Too Much?: Whole Session vs. First Query Behaviors in Task Type Prediction M. Mitsui, ..., and C. Shah The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval 2018 - 11 citations - Show abstract - Cite - PDF 0.6% topic match

0.6%

4.0

2009

[316] Standard parameters for searching behaviour in search engines and their empirical evaluation Nadine Höchstötter and M. Koch Journal of Information Science 2009 - 62 citations - Show abstract - Cite 0.6% topic match

0.5%

0.8

2016

[318] LifeBook: A Mobile Personal Information Management System on the Cloud R. Francese, ..., and G. Tortora Proceedings of the International Working Conference on Advanced Visual Interfaces 2016 - 7 citations - Show abstract - Cite 0.5% topic match

0.5%

0.9

1998

[319] A Simulation of Partial Information Use in Decision Making: Implications for DSS Design Ahmer Karim, ..., and W. C. Perkins Decision Sciences 1998 - 24 citations - Show abstract - Cite 0.5% topic match

0.5%

10.4

2013

[320] Beyond clicks: query reformulation as a predictor of search satisfaction Ahmed Hassan Awadallah, ..., and Bill Ramsey Proceedings of the 22nd ACM international conference on Information & Knowledge Management 2013 - 113 citations - Show abstract - Cite 0.5% topic match

0.5%

4.9

2014

[321] Discovering common motifs in cursor movement data for improving web search Dmitry Lagun, ..., and Eugene Agichtein Proceedings of the 7th ACM international conference on Web search and data mining 2014 - 52 citations - Show abstract - Cite 0.5% topic match

0.5%

3.0

2017

[322] The Good Left Undone: Advances and Challenges in Decentralizing Online Social Networks David Koll, ..., and Xiaoming Fu Comput. Commun. 2017 - 21 citations - Show abstract - Cite - PDF 0.5% topic match

0.5%

0.0

2021

[323] Fast Filtering of Search Results Sorted by Attribute F. M. Nardini, ..., and Roberto Trani ACM Transactions on Information Systems (TOIS) 2021 - 0 citations - Show abstract - Cite Abstract: Modern search services often provide multiple options to rank the search results, e.g., sort “by relevance”, “by price” or “by discount” in e-commerce. While the traditional rank by relevance effectively places the relevant results in the top positions of the results list, the rank by attribute could place many marginally relevant results in the head of the results list leading to poor user experience. In the past, this issue has been addressed by investigating the relevance-aware filtering problem, which asks to select the subset of results maximizing the relevance of the attribute-sorted list. Recently, an exact algorithm has been proposed to solve this problem optimally. However, the high computational cost of the algorithm makes it impractical for the Web search scenario, which is characterized by huge lists of results and strict time constraints. For this reason, the problem is often solved using efficient yet inaccurate heuristic algorithms. In this article, we first prove the performance bounds of the existing heuristics. We then propose two efficient and effective algorithms to solve the relevance-aware filtering problem. First, we propose OPT-Filtering, a novel exact algorithm that is faster than the existing state-of-the-art optimal algorithm. Second, we propose an approximate and even more efficient algorithm, ϵ-Filtering, which, given an allowed approximation error ϵ, finds a (1-ϵ)–optimal filtering, i.e., the relevance of its solution is at least (1-ϵ) times the optimum. We conduct a comprehensive evaluation of the two proposed algorithms against state-of-the-art competitors on two real-world public datasets. Experimental results show that OPT-Filtering achieves a significant speedup of up to two orders of magnitude with respect to the existing optimal solution, while ϵ-Filtering further improves this result by trading effectiveness for efficiency. In particular, experiments show that ϵ-Filtering can achieve quasi-optimal solutions while being faster than all state-of-the-art competitors in most of the tested configurations. 0.5% topic match

0.5%

1.1

2020

[324] Neural methods for effective, efficient, and exposure-aware information retrieval Bhaskar Mitra ACM SIGIR Forum 2020 - 4 citations - Show abstract - Cite - PDF Abstract: Neural networks with deep architectures have demonstrated significant performance improvements in computer vision, speech recognition, and natural language processing. The challenges in information retrieval (IR), however, are different from these other application areas. A common form of IR involves ranking of documents---or short passages---in response to keyword-based queries. Effective IR systems must deal with query-document vocabulary mismatch problem, by modeling relationships between different query and document terms and how they indicate relevance. Models should also consider lexical matches when the query contains rare terms---such as a person's name or a product model number---not seen during training, and to avoid retrieving semantically related but irrelevant results. In many real-life IR tasks, the retrieval involves extremely large collections---such as the document index of a commercial Web search engine---containing billions of documents. Efficient IR methods should take advantage of specialized IR data structures, such as inverted index, to efficiently retrieve from large collections. Given an information need, the IR system also mediates how much exposure an information artifact receives by deciding whether it should be displayed, and where it should be positioned, among other results. Exposure-aware IR systems may optimize for additional objectives, besides relevance, such as parity of exposure for retrieved items and content publishers. In this thesis, we present novel neural architectures and methods motivated by the specific needs and challenges of IR tasks. We ground our contributions with a detailed survey of the growing body of neural IR literature [Mitra and Craswell, 2018]. Our key contribution towards improving the effectiveness of deep ranking models is developing the Duet principle [Mitra et al., 2017] which emphasizes the importance of incorporating evidence based on both patterns of exact term matches and similarities between learned latent representations of query and document. To efficiently retrieve from large collections, we develop a framework to incorporate query term independence [Mitra et al., 2019] into any arbitrary deep model that enables large-scale precomputation and the use of inverted index for fast retrieval. In the context of stochastic ranking, we further develop optimization strategies for exposure-based objectives [Diaz et al., 2020]. Finally, this dissertation also summarizes our contributions towards benchmarking neural IR models in the presence of large training datasets [Craswell et al., 2019] and explores the application of neural methods to other IR tasks, such as query auto-completion. 0.5% topic match

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21.9

2009

[325] Characterizing the influence of domain expertise on web search behavior Ryen W. White, ..., and J. Teevan Web Search and Data Mining 2009 - 341 citations - Show abstract - Cite 0.5% topic match

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1.2

2010

[326] Agents, bookmarks and clicks: a topical model of web navigation Mark R. Meiss, ..., and F. Menczer ACM Conference on Hypertext & Social Media 2010 - 18 citations - Show abstract - Cite - PDF 0.5% topic match

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8.3

2013

[327] Summaries, ranked retrieval and sessions: a unified framework for information access evaluation T. Sakai and Zhicheng Dou Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval 2013 - 92 citations - Show abstract - Cite 0.5% topic match

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31.9

2018

[328] Copa: Practical Delay-Based Congestion Control for the Internet V. Arun and Hari Balakrishnan Proceedings of the Applied Networking Research Workshop 2018 - 196 citations - Show abstract - Cite 0.5% topic match

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60.0

2011

[329] Understanding the impact of video quality on user engagement Florin Dobrian, ..., and Hui Zhang Proceedings of the ACM SIGCOMM 2011 conference 2011 - 784 citations - Show abstract - Cite 0.5% topic match

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131.9

1983

[330] The psychology of human-computer interaction S. Card, ..., and A. Newell https://doi.org/10.2307/1422176 1983 - 5500 citations - Show abstract - Cite 0.5% topic match

0.5%

10.2

2011

[331] Find it if you can: a game for modeling different types of web search success using interaction data Mikhail S. Ageev, ..., and Eugene Agichtein Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval 2011 - 134 citations - Show abstract - Cite 0.5% topic match

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0.7

2014

[332] In small chunks or all at once? User preferences of network delays in web browsing sessions Nazrul Islam, ..., and M. Fiedler 2014 IEEE International Conference on Communications Workshops (ICC) 2014 - 7 citations - Show abstract - Cite - PDF 0.5% topic match

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3.2

2021

[333] Learnings from a Retail Recommendation System on Billions of Interactions at bol.com Barrie Kersbergen and Sebastian Schelter 2021 IEEE 37th International Conference on Data Engineering (ICDE) 2021 - 11 citations - Show abstract - Cite - PDF 0.5% topic match

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110.1

2007

[334] Development and Validation of an Internationally Reliable Short-Form of the Positive and Negative Affect Schedule (PANAS) E. Thompson Journal of Cross-Cultural Psychology 2007 - 1929 citations - Show abstract - Cite 0.5% topic match

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2.4

2022

[335] CoSearcher: studying the effectiveness of conversational search refinement and clarification through user simulation Alexandre Salle, ..., and Eugene Agichtein Information Retrieval Journal 2022 - 6 citations - Show abstract - Cite 0.5% topic match

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1.4

2009

[336] Searching for good mood: Examining relationships between search task and mood Irene Lopatovska ASIS&T Annual Meeting 2009 - 22 citations - Show abstract - Cite - PDF 0.5% topic match

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5.5

2009

[337] Classifying and Characterizing Query Intent Azin Ashkan, ..., and Qi Guo European Conference on Information Retrieval 2009 - 85 citations - Show abstract - Cite 0.5% topic match

0.4%

1.4

2021

[338] Engaging interaction and long-term engagement with WhatsApp in an everyday life context: exploratory study Juan-Antonio Martínez-Comeche and I. Ruthven J. Documentation 2021 - 5 citations - Show abstract - Cite - PDF 0.4% topic match

0.4%

47.8

2015

[339] The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections R. Epstein and Ronald E. Robertson Proceedings of the National Academy of Sciences 2015 - 435 citations - Show abstract - Cite - PDF Abstract: Significance We present evidence from five experiments in two countries suggesting the power and robustness of the search engine manipulation effect (SEME). Specifically, we show that (i) biased search rankings can shift the voting preferences of undecided voters by 20% or more, (ii) the shift can be much higher in some demographic groups, and (iii) such rankings can be masked so that people show no awareness of the manipulation. Knowing the proportion of undecided voters in a population who have Internet access, along with the proportion of those voters who can be influenced using SEME, allows one to calculate the win margin below which SEME might be able to determine an election outcome. Internet search rankings have a significant impact on consumer choices, mainly because users trust and choose higher-ranked results more than lower-ranked results. Given the apparent power of search rankings, we asked whether they could be manipulated to alter the preferences of undecided voters in democratic elections. Here we report the results of five relevant double-blind, randomized controlled experiments, using a total of 4,556 undecided voters representing diverse demographic characteristics of the voting populations of the United States and India. The fifth experiment is especially notable in that it was conducted with eligible voters throughout India in the midst of India’s 2014 Lok Sabha elections just before the final votes were cast. The results of these experiments demonstrate that (i) biased search rankings can shift the voting preferences of undecided voters by 20% or more, (ii) the shift can be much higher in some demographic groups, and (iii) search ranking bias can be masked so that people show no awareness of the manipulation. We call this type of influence, which might be applicable to a variety of attitudes and beliefs, the search engine manipulation effect. Given that many elections are won by small margins, our results suggest that a search engine company has the power to influence the results of a substantial number of elections with impunity. The impact of such manipulations would be especially large in countries dominated by a single search engine company. 0.4% topic match

0.4%

0.0

2018

[340] Sampling-based Techniques for Interactive Exploration of Large Datasets N. Kamat Journal Not Provided 2018 - 0 citations - Show abstract - Cite 0.4% topic match

0.4%

2.5

2014

[341] Exploiting temporal information in Web search Sheng Lin, ..., and Lihua Yue Expert Syst. Appl. 2014 - 26 citations - Show abstract - Cite 0.4% topic match

0.4%

14.0

2015

[342] Klotski: Reprioritizing Web Content to Improve User Experience on Mobile Devices Michael Butkiewicz, ..., and Vyas Sekar Symposium on Networked Systems Design and Implementation 2015 - 131 citations - Show abstract - Cite 0.4% topic match

0.4%

16.4

2012

[343] User see, user point: gaze and cursor alignment in web search Jeff Huang, ..., and Georg Buscher Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 2012 - 203 citations - Show abstract - Cite 0.4% topic match

0.4%

0.0

2015

[344] Narrowing down the debugging space of slow search response time Dapeng Liu, ..., and Mei Feng 2015 IEEE 34th International Performance Computing and Communications Conference (IPCCC) 2015 - 0 citations - Show abstract - Cite 0.4% topic match

0.4%

0.7

2020

[345] All but one Jörn Kuhlenkamp, ..., and Dominik Ernst ACM SIGAPP Applied Computing Review 2020 - 3 citations - Show abstract - Cite 0.4% topic match

0.4%

0.2

2012

[346] Cognitive consequences of search D. Kelly International Conference on Information Interaction in Context 2012 - 3 citations - Show abstract - Cite 0.4% topic match

0.4%

0.0

2024

[347] Accelerating BFT Database with Transaction Reconstruction Aoi Kida and Hideyuki Kawashima 2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) 2024 - 0 citations - Show abstract - Cite 0.4% topic match

0.4%

2.9

2010

[348] Reconsideration of the simulated work task situation: a context instrument for evaluation of information retrieval interaction Pia Borlund and J. Schneider International Conference on Information Interaction in Context 2010 - 41 citations - Show abstract - Cite 0.4% topic match

0.4%

0.1

2016

[349] Total Recall: Blue Sky on Mars C. Clarke, ..., and Adam Roegiest Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval 2016 - 1 citations - Show abstract - Cite 0.4% topic match

0.4%

10.7

2011

[350] Learning to re-rank: query-dependent image re-ranking using click data Vidit Jain and M. Varma The Web Conference 2011 - 144 citations - Show abstract - Cite 0.4% topic match

0.4%

5.4

1995

[351] The effects of filled waiting time and service provider control over the delay on evaluations of service Shirley Taylor Journal of the Academy of Marketing Science 1995 - 156 citations - Show abstract - Cite 0.4% topic match

0.4%

0.0

2018

[352] Dynamic cost-effective social network data placement and replication in the cloud Hourieh Khalajzadeh Journal Not Provided 2018 - 0 citations - Show abstract - Cite 0.4% topic match

0.4%

2.6

2021

[353] Investigating the Influence of Ads on User Search Performance, Behaviour, and Experience during Information Seeking Olivia Foulds, ..., and Martin Halvey Proceedings of the 2021 Conference on Human Information Interaction and Retrieval 2021 - 9 citations - Show abstract - Cite - PDF 0.4% topic match

0.4%

3.2

2021

[354] How Level of Explanation Detail Affects Human Performance in Interpretable Intelligent Systems: A Study on Explainable Fact Checking Rhema Linder, ..., and Xia Hu Applied AI Letters 2021 - 9 citations - Show abstract - Cite 0.4% topic match

0.4%

1.5

2019

[355] Low Latency for Cloud Data Management Felix Gessert Journal Not Provided 2019 - 8 citations - Show abstract - Cite Abstract: With the rise of scalable, distributed web applications, latency has become a fundamental challenge for cloud data management. The delays caused by accessing data from cloud services often dominate the performance of web and mobile applications. While modern data management systems address the need for higher scalability and fault tolerance, low latency remains an open issue. How can low-latency queries and reads be enabled without sacrificing central data management abstractions such as consistency levels and transactional isolation? In this thesis, we investigate caching in cloud data management for dynamic data ranging from database objects to complex query results. In the context of distributed systems, achieving reads that are both fast and consistent is tied to the challenge of maintaining fresh replicated data in proximity to clients. Therefore, we propose the data management platform Orestes that enhances existing NoSQL database systems with low latency. Orestes introduces several new techniques to substantially improve latency in cloud data management. First, it leverages the expiration-based model of web caches available all over the world through a novel cache coherence scheme – Cache Sketches. Our approach thus makes caching applicable to highly volatile cloud data while maintaining rigorous consistency levels. Second, transactions are a key concept often sacrificed in state-of-the-art systems for performance reasons. Therefore, we propose an approach for horizontally scalable, low-latency ACID transactions that can be added on top of existing database systems. Third, to enable polyglot persistence, we survey the field of scalable data management and derive a novel classification scheme that relates database implementation techniques to functional and non-functional guarantees. By combining these findings in a unified data management interface, Orestes can provide existing systems as a scalable, low-latency Database-as-a-Service. Fourth, with the design of a polyglot persistence mediator, we argue that the selection of suitable database systems for a given set of requirements can be automated based on service level agreements. Finally, we provide evidence that for typical web applications and database workloads, our approach can improve latency by more than an order of magnitude compared to traditional cloud-hosted backends and database systems. Mit der Verbreitung skalierbarer und verteilter Webanwendungen sind Zugriffslatenzen zu einer grundlegenden Herausforderung fur das Cloud Data Management geworden. Die Verzogerungen bei der Abfrage von Daten aus Cloud-Diensten dominieren oft die Performance von Web- und mobilen Anwendungen. Wahrend moderne Datenmanagementsysteme den Bedarf nach hoherer Skalierbarkeit und Fehlertoleranz adressieren, bleibt die Latenz eine offene Herausforderung. Wie konnen Lesezugriffe und Queries mit geringer Latenz beantwortet werden, ohne dabei zentrale Abstraktionen des Datenmanagements wie Konsistenzstufen und transaktionale Isolation aufzugeben? In dieser Arbeit untersuchen wir Caching im Cloud Data Management fur dynamische Daten von Datenbankobjekten bis hin zu komplexen Query-Ergebnissen. Im Kontext verteilter Systeme sind schnelle und korrekte Lesezugriffe mit der Herausforderung verbunden, replizierte Daten konsistent in physischer Nahe zu Usern vorzuhalten. Aus diesem Grund fuhren wir die Data Management-Plattform Orestes ein, um die Latenzen bestehender NoSQL-Datenbanksysteme zu verringern. Orestes verwendet mehrere neue Techniken, mit denen die Latenzen lesender Operationen im Cloud Data Management erheblich verbessert werden. Erstens nutzt es das expirationsbasierte Modell von Web-Caches, die uber ein neues Cachekoharenz-Verfahren namens Cache Sketches aktuell gehalten werden. Unser Ansatz macht Caching somit auch fur sehr volatile Cloud-Daten anwendbar und stellt dabei konfigurierbare Konsistenzgarantien sicher. Zweitens sind Transaktionen ein Kernkonzept des Datenmanagements, auf das in modernen Systemen oft aus Performancegrunden verzichtet wird. Daher schlagen wir einen Ansatz fur horizontal skalierbare ACID-Transaktionen mit geringen Latenzen vor, der auf bestehende Datenbanksysteme anwendbar ist. Drittens leiten wir fur polyglotte Persistenz durch eine genaue Analyse verfugbarer Ansatze ein Klassifikationsschema ab, das die Implementierungstechniken der Datenbanksysteme mit funktionalen und nicht-funktionalen Garantien in Beziehung setzt. Durch die Anwendung der Systematik auf eine vereinheitlichte Datenmanagement- Schnittstelle kann Orestes bestehende Systeme als skalierbares Database-as-a-Service mit geringer Latenz anbieten. Viertens zeigen wir mit dem Design eines Polyglot Persistence Mediators, dass die Auswahl geeigneter Datenbanksysteme auf Basis von Service Level Agreements automatisiert werden kann. Abschliesend belegen wir quantitativ, dass unser Ansatz fur typische Webanwendungen und Datenbank-Workloads die Latenz um mehr als eine Grosenordnung gegenuber herkommlichen Backends und Datenbanksystemen verbessert. 0.4% topic match

0.4%

0.0

2023

[356] Privacy engineering through obfuscation Ero Balsa ArXiv 2023 - 0 citations - Show abstract - Cite - PDF 0.4% topic match

0.4%

0.2

2015

[357] Queuing Theory-based Latency/Power Tradeoff Models for Replicated Search Engines Ana Freire, ..., and Fidel Cacheda J. Univers. Comput. Sci. 2015 - 2 citations - Show abstract - Cite - PDF 0.4% topic match

0.4%

1.1

2017

[358] Foraging patterns in online searches. Xiangwen Wang and M. Pleimling Physical review. E 2017 - 8 citations - Show abstract - Cite - PDF 0.4% topic match

0.4%

16.3

2019

[359] Dynamic TCP Initial Windows and Congestion Control Schemes Through Reinforcement Learning Xiaohui Nie, ..., and Dan Pei IEEE Journal on Selected Areas in Communications 2019 - 89 citations - Show abstract - Cite 0.4% topic match

0.4%

0.2

2011

[360] A Four Group Cross-Over Design for Measuring Irreversible Treatments on Web Search Tasks Li Ma, ..., and D. Russell 2011 44th Hawaii International Conference on System Sciences 2011 - 3 citations - Show abstract - Cite 0.4% topic match

0.4%

2.6

2019

[361] Unleashing the Scalability Potential of Power-Constrained Data Center in the Microservice Era Xiaofeng Hou, ..., and M. Guo Proceedings of the 48th International Conference on Parallel Processing 2019 - 13 citations - Show abstract - Cite 0.4% topic match

0.4%

0.0

2018

[362] Evaluating the correlation between site speed and its effect on conversion rates for Norwegian Air Shuttle ASA Ali Vindenes Fetouni Journal Not Provided 2018 - 0 citations - Show abstract - Cite 0.4% topic match

0.4%

0.1

2015

[363] Performance of mobile GIS in conjunction withinternet bandwidth in rural areas Jón Ágúst Reynisson Journal Not Provided 2015 - 1 citations - Show abstract - Cite 0.4% topic match

0.3%

0.3

2018

[364] Evaluation of Information Retrieval Systems Using Structural Equation Modelling Massimo Melucci ArXiv 2018 - 2 citations - Show abstract - Cite - PDF 0.3% topic match

0.3%

7.0

1994

[365] The effect of information presentation on decision making: A cost-benefit analysis I. Vessey Inf. Manag. 1994 - 212 citations - Show abstract - Cite 0.3% topic match

0.3%

8.1

2018

[366] P-Store: An Elastic Database System with Predictive Provisioning Rebecca Taft, ..., and Francisco Jose Andrade Proceedings of the 2018 International Conference on Management of Data 2018 - 51 citations - Show abstract - Cite 0.3% topic match

0.3%

4.7

2013

[368] Personalized models of search satisfaction Ahmed Hassan Awadallah and Ryen W. White Proceedings of the 22nd ACM international conference on Information & Knowledge Management 2013 - 51 citations - Show abstract - Cite - PDF 0.3% topic match

0.3%

0.0

2023

[369] What Lies Beneath? Exploring the Impact of Underlying AI Model Updates in AI-Infused Systems Vikram Mohanty, ..., and Kurt Luther ArXiv 2023 - 0 citations - Show abstract - Cite - PDF 0.3% topic match

0.3%

0.0

2018

[370] REAL-TIME BROWSING ASSISTANT ON WEB S. T. Zuhori and James Miller IADIS INTERNATIONAL JOURNAL ON WWW/INTERNET 2018 - 0 citations - Show abstract - Cite 0.3% topic match

0.3%

4.2

2018

[371] Time Well Spent. M. Schlögl Journal of palliative medicine 2018 - 26 citations - Show abstract - Cite 0.3% topic match

0.3%

1.0

2018

[372] The Broad View of Task Type Using Path Analysis M. Mitsui and C. Shah Proceedings of the 2018 ACM SIGIR International Conference on Theory of Information Retrieval 2018 - 6 citations - Show abstract - Cite - PDF 0.3% topic match

0.3%

10.3

2016

[373] An In-depth Study of Mobile Browser Performance Javad Nejati and A. Balasubramanian Proceedings of the 25th International Conference on World Wide Web 2016 - 87 citations - Show abstract - Cite 0.3% topic match

0.3%

6.4

2017

[375] Making Sense of Conflicting Science Information: Exploring Bias in the Search Engine Result Page Alamir Novin and E. Meyers Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval 2017 - 48 citations - Show abstract - Cite 0.3% topic match

0.3%

0.5

2022

[376] Niyama: Node scheduling for cloud workloads with resource isolation Meghana Thiyyakat, ..., and D. Sitaram Concurrency and Computation: Practice and Experience 2022 - 1 citations - Show abstract - Cite 0.3% topic match

0.3%

24.0

1990

[377] Improving a human-computer dialogue R. Molich and J. Nielsen Commun. ACM 1990 - 829 citations - Show abstract - Cite 0.3% topic match

0.3%

6.6

2013

[378] Absence time and user engagement: evaluating ranking functions G. Dupret and M. Lalmas Proceedings of the sixth ACM international conference on Web search and data mining 2013 - 77 citations - Show abstract - Cite 0.3% topic match

0.3%

2.9

2016

[379] Is This Your Final Answer?: Evaluating the Effect of Answers on Good Abandonment in Mobile Search Kyle Williams, ..., and Madian Khabsa Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval 2016 - 24 citations - Show abstract - Cite 0.3% topic match

0.3%

0.0

2016

[380] Filtering News from Document Streams: Evaluation Aspects and Modeled Stream Utility G. Baruah Journal Not Provided 2016 - 0 citations - Show abstract - Cite Abstract: Events like hurricanes, earthquakes, or accidents can impact a large number of people. Not only are people in the immediate vicinity of the event affected, but concerns about their well-being are shared by the local government and well-wishers across the world. The latest information about news events could be of use to government and aid agencies in order to make informed decisions on providing necessary support, security and relief. The general public avails of news updates via dedicated news feeds or broadcasts, and lately, via social media services like Facebook or Twitter. Retrieving the latest information about newsworthy events from the world-wide web is thus of importance to a large section of society. As new content on a multitude of topics is continuously being published on the web, specific event related information needs to be filtered from the resulting stream of documents. We present in this thesis, a user-centric evaluation measure for evaluating systems that filter news related information from document streams. Our proposed evaluation measure, Modeled Stream Utility (MSU), models users accessing information from a stream of sentences produced by a news update filtering system. The user model allows for simulating a large number of users with different characteristic stream browsing behavior. Through simulation, MSU estimates the utility of a system for an average user browsing a stream of sentences. Our results show that system performance is sensitive to a user population’s stream browsing behavior and that existing evaluation metrics correspond to very specific types of user behavior. To evaluate systems that filter sentences from a document stream, we need a set of judged sentences. This judged set is a subset of all the sentences returned by all systems, and is typically constructed by pooling together the highest quality sentences, as determined by respective system assigned scores for each sentence. Sentences in the pool are manually assessed and the resulting set of judged sentences is then used to compute system performance metrics. In this thesis, we investigate the effect of including duplicates of judged sentences, into the judged set, on system performance evaluation. We also develop an alternative pooling methodology, that given the MSU user model, selects sentences for pooling based on the probability of a sentences being read by modeled users. Our research lays the foundation for interesting future work for utilizing user-models in different aspects of evaluation of stream filtering systems. The MSU measure enables incorporation of different user models. Furthermore, the applicability of MSU could be extended through calibration based on user behavior. 0.3% topic match

0.3%

1.7

1986

[381] System response time effects on user productivity Gale Martin and K. Corl Behaviour & Information Technology 1986 - 66 citations - Show abstract - Cite 0.3% topic match

0.3%

55.8

2003

[382] MARC HASSENZAHL CHAPTER 3 The Thing and I: Understanding the Relationship Between User and Product Marc Hassenzahl Journal Not Provided 2003 - 1211 citations - Show abstract - Cite 0.3% topic match

0.3%

1.2

2019

[383] Correlations between Human Performance in Information Seeking, Information Integration, and Overall Process in Diagnostic Tasks Xi Lyu and Zhizhong Li International Journal of Human–Computer Interaction 2019 - 6 citations - Show abstract - Cite 0.3% topic match

0.3%

0.2

2016

[384] Web prefetching of smart wireless access point Hui Li, ..., and Q. Lin 2016 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI) 2016 - 2 citations - Show abstract - Cite 0.3% topic match

0.3%

0.0

2019

[385] STOP Formulate Query Click Link Judge Document Relevance Read Document Scan Snippeti ii iii ivv vi Figure 1 David Maxwell and L. Azzopardi Journal Not Provided 2019 - 0 citations - Show abstract - Cite 0.3% topic match

0.3%

2.8

2015

[386] Terms, Topics & Tasks: Enhanced User Modelling for Better Personalization Rishabh Mehrotra and Emine Yilmaz Proceedings of the 2015 International Conference on The Theory of Information Retrieval 2015 - 25 citations - Show abstract - Cite 0.3% topic match

0.3%

12.8

2020

[387] Analyzing the Effects of "People also ask" on Search Behaviors and Beliefs Suppanut Pothirattanachaikul, ..., and Masatoshi Yoshikawa Proceedings of the 31st ACM Conference on Hypertext and Social Media 2020 - 53 citations - Show abstract - Cite 0.3% topic match

0.3%

69.0

2018

[388] Demographics and Dynamics of Mechanical Turk Workers D. Difallah, ..., and Panagiotis G. Ipeirotis Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining 2018 - 455 citations - Show abstract - Cite 0.3% topic match

0.2%

0.3

2013

[389] A Reference Model For Mobile Product Information Systems Yvonne Hufenbach and K. Pousttchi Journal Not Provided 2013 - 3 citations - Show abstract - Cite 0.2% topic match

0.2%

187.8

1979

[390] Metacognition and Cognitive Monitoring: A New Area of Cognitive-Developmental Inquiry. J. Flavell American Psychologist 1979 - 8581 citations - Show abstract - Cite 0.2% topic match

0.2%

1.1

2006

[391] Optimisation mechanism for web search results using topic knowledge Y. Panagis, ..., and A. Tsakalidis Int. J. Knowl. Learn. 2006 - 21 citations - Show abstract - Cite 0.2% topic match

0.2%

14.3

2011

[392] Augmenting web pages and search results to support credibility assessment Julia Schwarz and M. Morris Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 2011 - 191 citations - Show abstract - Cite 0.2% topic match

0.2%

8.3

2013

[393] A systematic review of interactive information retrieval evaluation studies, 1967-2006 D. Kelly and Cassidy R. Sugimoto J. Assoc. Inf. Sci. Technol. 2013 - 95 citations - Show abstract - Cite 0.2% topic match

0.2%

0.4

2011

[394] Scrolling and pagination for within document searching: The impact of screen size and interaction style L. Marcial and B. Hemminger ASIS&T Annual Meeting 2011 - 5 citations - Show abstract - Cite 0.2% topic match

0.2%

2.9

1966

[395] Aslib Cranfield research project - Factors determining the performance of indexing systems; Volume 1, Design; Part 2, Appendices C. Cleverdon, ..., and M. Keen Journal Not Provided 1966 - 169 citations - Show abstract - Cite 0.2% topic match

0.2%

0.1

2015

[396] Liberating Virtual Machines from Physical Boundaries through Execution Knowledge Yoshihisa Abe Journal Not Provided 2015 - 1 citations - Show abstract - Cite 0.2% topic match

0.2%

None

[397] ScholarWorks ScholarWorks Michael D. Ekstrand and J. Konstan Journal Not Provided None - 37 citations - Show abstract - Cite 0.2% topic match

0.2%

3.2

2011

[398] Energy-price-driven query processing in multi-center web search engines Enver Kayaaslan, ..., and C. Aykanat Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval 2011 - 42 citations - Show abstract - Cite - PDF 0.2% topic match

0.2%

6.3

2019

[399] User engagement for mid-air haptic interactions with digital signage Hannah Limerick, ..., and Jörg Müller Proceedings of the 8th ACM International Symposium on Pervasive Displays 2019 - 33 citations - Show abstract - Cite 0.2% topic match

0.2%

94.9

1993

[400] Usability engineering Jakob Nielsen https://doi.org/10.1016/c2009-0-21512-1 1993 - 3007 citations - Show abstract - Cite 0.2% topic match

0.2%

5.2

2023

[401] A Personalized Neighborhood-based Model for Within-basket Recommendation in Grocery Shopping Mozhdeh Ariannezhad, ..., and M. de Rijke Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining 2023 - 8 citations - Show abstract - Cite - PDF 0.2% topic match

0.2%

6.2

2019

[402] Knowledge-Context in Search Systems: Toward Information-Literate Actions Catherine L. Smith and Soo Young Rieh Proceedings of the 2019 Conference on Human Information Interaction and Retrieval 2019 - 34 citations - Show abstract - Cite 0.2% topic match

0.2%

6.2

2014

[403] Querying big graphs within bounded resources W. Fan, ..., and Yinghui Wu Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data 2014 - 63 citations - Show abstract - Cite - PDF 0.2% topic match

0.2%

0.3

2018

[404] Study of Relevance and Effort across Devices Manisha Verma, ..., and Nick Craswell Proceedings of the 2018 Conference on Human Information Interaction & Retrieval 2018 - 2 citations - Show abstract - Cite - PDF 0.2% topic match

0.2%

82.7

1991

[405] Unified Theories of Cognition Richard Reviewer-Granger Journal of Cognitive Neuroscience 1991 - 2745 citations - Show abstract - Cite 0.2% topic match

0.2%

10.3

2016

[406] EYEORG: A Platform For Crowdsourcing Web Quality Of Experience Measurements Matteo Varvello, ..., and K. Papagiannaki Proceedings of the 12th International on Conference on emerging Networking EXperiments and Technologies 2016 - 80 citations - Show abstract - Cite - PDF 0.2% topic match

0.2%

3.0

2008

[407] The good and the bad system: does the test collection predict users' effectiveness? A. Al-Maskari, ..., and Eija Airio Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2008 - 48 citations - Show abstract - Cite 0.2% topic match

0.2%

0.0

2019

[408] M ay 2 01 9 Evaluating Variable-Length Multiple-Option Lists in Chatbots and Mobile Search Pepa Atanasova Pepa Atanasova and F. Sebastiani Journal Not Provided 2019 - 0 citations - Show abstract - Cite 0.2% topic match

0.2%

1.1

2020

[409] Analyzing Wikipedia Users’ Perceived Quality of Experience: A Large-Scale Study Flavia Salutari, ..., and Dario Rossi IEEE Transactions on Network and Service Management 2020 - 5 citations - Show abstract - Cite 0.2% topic match

0.2%

44.2

2012

[410] Video stream quality impacts viewer behavior: inferring causality using quasi-experimental designs Shankar Krishnan and R. Sitaraman Proceedings of the 2012 Internet Measurement Conference 2012 - 522 citations - Show abstract - Cite 0.2% topic match

0.2%

7.4

2022

[411] Duplicate Bug Report Detection: How Far Are We? Ting Zhang, ..., and Lingxiao Jiang ACM Transactions on Software Engineering and Methodology 2022 - 13 citations - Show abstract - Cite - PDF 0.2% topic match

0.2%

10.4

2015

[412] Scalability Challenges in Web Search Engines B. B. Cambazoglu and R. Baeza-Yates Advanced Topics in Information Retrieval 2015 - 91 citations - Show abstract - Cite 0.2% topic match

0.2%

7.7

1899

[413] Response time in man-computer conversational transactions Robert B. Miller Proceedings of the December 9-11, 1968, fall joint computer conference, part I 1899 - 962 citations - Show abstract - Cite - PDF 0.2% topic match

0.2%

5.4

2021

[414] The role of user context in the design of mobile map applications M. Bartling, ..., and Karl Atzmanstorfer Cartography and Geographic Information Science 2021 - 17 citations - Show abstract - Cite - PDF 0.2% topic match

0.2%

12.6

2010

[415] Beyond position bias: examining result attractiveness as a source of presentation bias in clickthrough data Yisong Yue, ..., and H. Roehrig The Web Conference 2010 - 181 citations - Show abstract - Cite 0.2% topic match

0.2%

0.0

2023

[416] Many are Better than One: Algorithm Selection for Faster Top-K Retrieval Gabriel Tolosa and Antonio Mallia Inf. Process. Manag. 2023 - 0 citations - Show abstract - Cite 0.2% topic match

0.2%

0.0

2015

[417] Slow Search: Improving Information Retrieval Using Human Assistance J. Teevan Proceedings of the 24th ACM International on Conference on Information and Knowledge Management 2015 - 0 citations - Show abstract - Cite 0.2% topic match

0.2%

1.5

2019

[418] EMPATIA: A Multichannel Platform for Participatory Budgeting B. Sousa, ..., and V. Weerakkody Int. J. Electron. Gov. Res. 2019 - 8 citations - Show abstract - Cite 0.2% topic match

0.2%

5.1

2020

[419] Offline Evaluation by Maximum Similarity to an Ideal Ranking C. Clarke, ..., and Alexandra Vtyurina Proceedings of the 29th ACM International Conference on Information & Knowledge Management 2020 - 20 citations - Show abstract - Cite 0.2% topic match

0.2%

5.0

2018

[420] Boosting Search Performance Using Query Variations R. Benham, ..., and J. Culpepper ACM Transactions on Information Systems (TOIS) 2018 - 29 citations - Show abstract - Cite - PDF 0.2% topic match

0.2%

2.6

1996

[422] What is wrong with the World-Wide Web?: a diagnosis of some problems and prescription of some remedies Nancy J. Lightner, ..., and G. Salvendy Ergonomics 1996 - 74 citations - Show abstract - Cite 0.2% topic match

0.2%

4.9

1996

[423] Top ten mistakes in web design J. Nielsen https://doi.org/10.1201/9780849375477.ch266 1996 - 140 citations - Show abstract - Cite 0.2% topic match

0.2%

15.8

2016

[424] QoE matters more than QoS: Why people stop watching cat videos Hyunwoo Nam, ..., and H. Schulzrinne IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications 2016 - 133 citations - Show abstract - Cite 0.2% topic match

0.2%

7.0

2020

[425] Benchmarking elasticity of FaaS platforms as a foundation for objective-driven design of serverless applications Jörn Kuhlenkamp, ..., and Daniel Wenzel Proceedings of the 35th Annual ACM Symposium on Applied Computing 2020 - 31 citations - Show abstract - Cite 0.2% topic match

0.2%

1.6

2023

[426] Multi-Factor Credential Hashing for Asymmetric Brute-Force Attack Resistance V. Nair and D. Song 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P) 2023 - 2 citations - Show abstract - Cite - PDF 0.2% topic match

0.2%

None

[427] Inter-domain Incentives and Internet Architecture Inter-domain Incentives and Internet Architecture J. Rajahalme, ..., and Lixin Gao Journal Not Provided None - 0 citations - Show abstract - Cite 0.2% topic match

0.1%

None

[428] Some Myths, Some Truths, and Some Hope Waqar Aqeel, ..., and Ankit Singla Journal Not Provided None - 0 citations - Show abstract - Cite 0.1% topic match

0.1%

4.8

2012

[429] Domain bias in web search Samuel Ieong, ..., and Li Zhang Web Search and Data Mining 2012 - 60 citations - Show abstract - Cite 0.1% topic match

0.1%

1.6

1999

[430] The TREC-8 Query Track C. Buckley and Janet A. Walz Text Retrieval Conference 1999 - 41 citations - Show abstract - Cite 0.1% topic match

0.1%

6.8

2015

[431] Influence of Vertical Result in Web Search Examination Zeyang Liu, ..., and Shaoping Ma Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval 2015 - 62 citations - Show abstract - Cite 0.1% topic match

0.1%

0.0

2023

[432] Fine-grained HTTP/3 prioritization via reinforcement learning Ka-Yoon Wong and Lin Cui Comput. Networks 2023 - 0 citations - Show abstract - Cite 0.1% topic match

0.1%

6.6

2020

[433] Models Versus Satisfaction: Towards a Better Understanding of Evaluation Metrics Fan Zhang, ..., and Shaoping Ma Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval 2020 - 27 citations - Show abstract - Cite 0.1% topic match

0.1%

13.1

2013

[434] Video Stream Quality Impacts Viewer Behavior: Inferring Causality Using Quasi-Experimental Designs Shankar Krishnan and R. Sitaraman IEEE/ACM Transactions on Networking 2013 - 141 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

0.7

2020

[435] Fast and Scalable Cloud Data Management Felix Gessert, ..., and N. Ritter Fast and Scalable Cloud Data Management 2020 - 3 citations - Show abstract - Cite 0.1% topic match

0.1%

0.1

2011

[436] Dynamic Analysis of Chinese Search Engine User Behavior Liu Jian Journal of Chinese information processing 2011 - 1 citations - Show abstract - Cite 0.1% topic match

0.1%

3.2

2022

[437] Users and Contemporary SERPs: A (Re-)Investigation Nirmal Roy, ..., and C. Hauff Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval 2022 - 7 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

1.9

2019

[438] Siva - The IPFS Search Engine Nawras Khudhur and S. Fujita 2019 Seventh International Symposium on Computing and Networking (CANDAR) 2019 - 10 citations - Show abstract - Cite 0.1% topic match

0.1%

0.1

2016

[439] Ten Blue Links on Mars C. Clarke, ..., and Adam Roegiest Proceedings of the 26th International Conference on World Wide Web 2016 - 1 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

1.0

2019

[440] Using Principal Component Analysis to Better Understand Behavioral Measures and their Effects Jaime Arguello and Anita Crescenzi Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval 2019 - 5 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

12.9

2004

[441] Search engine coverage bias: evidence and possible causes L. Vaughan and M. Thelwall Inf. Process. Manag. 2004 - 263 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

0.0

2022

[442] A Deep Learning-based Prefetching Approach to Enable Scalability for Data-intensive Applications Tolga Büyüktanir and M. Aktaş 2022 IEEE International Conference on Big Data (Big Data) 2022 - 0 citations - Show abstract - Cite 0.1% topic match

0.1%

4.8

2018

[443] Optimizing Query Evaluations Using Reinforcement Learning for Web Search Corby Rosset, ..., and Saurabh Tiwary The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval 2018 - 31 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

210.5

2002

[444] Cumulated gain-based evaluation of IR techniques K. Järvelin and Jaana Kekäläinen ACM Trans. Inf. Syst. 2002 - 4618 citations - Show abstract - Cite 0.1% topic match

0.1%

1.5

2024

[445] Online dynamic replication and placement algorithms for cost optimization of online social networks in two-tier multi-cloud Ali Y. Aldailamy, ..., and Waidah Ismail J. Netw. Comput. Appl. 2024 - 1 citations - Show abstract - Cite 0.1% topic match

0.1%

None

[446] Don’t Forget the User: It’s Time to Rethink Network Measurements No author found Journal Not Provided None - 0 citations - Show abstract - Cite 0.1% topic match

0.1%

0.5

2013

[447] How do users grow up along with search engines?: a study of long-term users' behavior Jian Liu, ..., and Shaoping Ma Proceedings of the 22nd ACM international conference on Information & Knowledge Management 2013 - 5 citations - Show abstract - Cite 0.1% topic match

0.1%

3.4

2022

[448] Large-scale analysis of query logs to profile users for dataset search Romina Sharifpour, ..., and Xiuzhen Zhang J. Documentation 2022 - 8 citations - Show abstract - Cite 0.1% topic match

0.1%

119.3

2007

[449] The electrodermal system M. Dawson, ..., and D. L. Filion https://doi.org/10.1017/CBO9780511546396.007 2007 - 2090 citations - Show abstract - Cite 0.1% topic match

0.1%

1.3

2015

[450] Know Your Onions: Understanding the User Experience with the Knowledge Module in Web Search Ioannis Arapakis, ..., and B. B. Cambazoglu Proceedings of the 24th ACM International on Conference on Information and Knowledge Management 2015 - 12 citations - Show abstract - Cite 0.1% topic match

0.1%

2.8

2022

[451] Distributed Latency Profiling through Critical Path Tracing Brian Eaton, ..., and N. Tas Queue 2022 - 7 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

1.8

2019

[452] Investigating the Impacts of Expectation Disconfirmation on Web Search Jiqun Liu and C. Shah Proceedings of the 2019 Conference on Human Information Interaction and Retrieval 2019 - 10 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

1.5

2024

[453] SEUPD@CLEF: Team Axolotl on Rumor Verification using Evidence from Authorities Andrea Pasin and Nicola Ferro Conference and Labs of the Evaluation Forum 2024 - 1 citations - Show abstract - Cite 0.1% topic match

0.1%

4.2

2019

[454] Measuring Web Latency and Rendering Performance: Method, Tools, and Longitudinal Dataset A. Asrese, ..., and J. Ott IEEE Transactions on Network and Service Management 2019 - 22 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

0.7

2022

[455] IOQP: A simple Impact-Ordered Query Processor written in Rust J. Mackenzie, ..., and L. Gallagher Biennial Conference on Design of Experimental Search & Information Retrieval Systems 2022 - 2 citations - Show abstract - Cite 0.1% topic match

0.1%

1.9

2015

[456] WWW=WAIT, WAIT, WAIT: EMOTIONAL REACTIONS TO WAITING ON THE INTERNET Gerard Ryan, ..., and M. Valverde Journal of Electronic Commerce Research 2015 - 17 citations - Show abstract - Cite Abstract: 1. IntroductionThis study examines the topic of waiting on the Internet. Academics, professionals and users have been complaining about the slowness of the Internet since the mid 90's [Chebat et al. 2010; Dabholkar & Sheng 2009; Dellaert & Kahn 1999; Sears et al. 1997; Tze-Hsien & Ching-Jui 2014]. Although the Internet is much faster nowadays, consumers' expectations have also increased significantly. We now expect instantaneous results from the Internet [Kedrosky 2006; Weatherhead 2014]. Just as waiting in everyday life is undesirable, waiting on the Internet produces negative effects on the Internet user experience, which in turn leads to negative word-of-mouth [Roman & Riquelme 2014]. The phenomenon of web rage has been widely reported in the popular press [Team Register 2014], while books and pop songs have been dedicated to the experience of waiting on the Internet [Bowman 2002; Ryan 2014]. It has been suggested that waiting online provokes negative feelings of frustration and impatience on the part of the user [Roman & Riquelme 2014; Eisenberg 2002], which can lead users to abandon web sites [Dabholkar & Sheng 2008; Kaufman-Scarborough & Lindquist 2002; Rajamma et al. 2009] and to develop negative attitudes towards them [Rose & Straub 2001]. Waiting on the Internet has also been linked been linked to a lack of trust in the security of web sites [Yoon 2002], to the interruption of the 'flow' experience [Rettie 2001; Van Beveren et al. 2003] and to problems in maintaining interactivity [Stewart & Pavlou 2002].Most of the existing studies on this topic focus on just one single type of online waiting situation, commonly labelled download delay, i.e. the delay involved in waiting for web pages to download and appear on the user's screen [Nah 2004; Rose & Straub 2001; Rose et al. 2003; Weinberg 2000; Weinberg et al. 2003]. From a marketing perspective this ignores a whole range of online waiting situations in online services that were identified and described by Ryan & Valverde [2005], including waiting for replies from customer support services, waiting for onscreen advertising to end, waiting to access traffic congested websites or for websites temporarily closed for maintenance. The overriding emphasis on measuring just tolerance of download time has left many questions unanswered and many gaps in our knowledge of the wider consumer experience while waiting on the Internet. Indeed, no previous study has examined the emotional or affective consequences of waiting on the Internet in any great detail. This gap in our knowledge and understanding of online consumer behaviour is surprising considering that from a marketing perspective, waiting on the Internet has been linked to serious issues including the loss of potential clients and the elimination of one of the main motivations for shopping online, i.e. timesaving and convenience [Foucault & Scheufele 2002; Rodriguez 2002,]. The objective of this paper is to identify and consider the emotional reactions of consumers when they experience waiting on the Internet.2. Literature reviewThis section examines the literature related to waiting on the Internet. Firstly, we examine the three main disciplines that consider this topic, Human Computer Interaction (HCI), Internet Quality of Service (QoS) and e-Services Marketing. Secondly, we examine the related literature on consumers' reactions to waiting in traditional (offline services) in order to consider the implications for research on waiting in online services. Thirdly, we examine the literature on emotions in order to consider the emotional reaction to waiting on the Internet.In HCI research, the concept of 'delay' has been studied since the early 1980's [Shneiderman 1984; Weiss et al. 1982]. It demonstrates that delays in the response of personal computers cause uncomfortable feelings of annoyance and frustration among users [Schleifer & Amick 1989]. … 0.1% topic match

0.1%

28.8

2011

[457] Quantification of YouTube QoE via Crowdsourcing T. Hossfeld, ..., and R. Schatz 2011 IEEE International Symposium on Multimedia 2011 - 367 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

30.0

2007

[458] What are you looking for?: an eye-tracking study of information usage in web search Edward Cutrell and Z. Guan Proceedings of the SIGCHI Conference on Human Factors in Computing Systems 2007 - 520 citations - Show abstract - Cite 0.1% topic match

0.1%

1.5

2020

[460] A Comparison of Supervised Learning to Match Methods for Product Search F. Sarvi, ..., and M. de Rijke ArXiv 2020 - 6 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

0.5

2014

[461] Applying the IS success model to mobile banking apps Tao Li Journal Not Provided 2014 - 5 citations - Show abstract - Cite 0.1% topic match

0.1%

1.4

2018

[462] Adapting to Access Locality via Live Data Migration in Globally Distributed Datastores Aleksey Charapko, ..., and M. Demirbas 2018 IEEE International Conference on Big Data (Big Data) 2018 - 8 citations - Show abstract - Cite 0.1% topic match

0.1%

4.1

2020

[463] Gemini: Learning to Manage CPU Power for Latency-Critical Search Engines Liang Zhou, ..., and K. K. Ramakrishnan 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO) 2020 - 16 citations - Show abstract - Cite 0.1% topic match

0.1%

0.2

2006

[464] Aggregating Subjective and Objective Measures of Web Search Quality using Modified Shimura Technique R. Ali and M. Beg 9th International Conference on Information Technology (ICIT'06) 2006 - 3 citations - Show abstract - Cite 0.1% topic match

0.1%

6.2

2020

[465] ANT-Man: Towards Agile Power Management in the Microservice Era Xiaofeng Hou, ..., and M. Guo SC20: International Conference for High Performance Computing, Networking, Storage and Analysis 2020 - 24 citations - Show abstract - Cite 0.1% topic match

0.1%

0.6

2010

[466] New measures for the evaluation of interactive information retrieval systems: Normalized task completion time and normalized user effectiveness Jing Cheng, ..., and P. Heidorn ASIS&T Annual Meeting 2010 - 8 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

8.6

2018

[467] Optimal Scheduling of VMs in Queueing Cloud Computing Systems With a Heterogeneous Workload Mian Guo, ..., and Wende Ke IEEE Access 2018 - 57 citations - Show abstract - Cite 0.1% topic match

0.1%

2.5

2022

[468] ShorTor: Improving Tor Network Latency via Multi-hop Overlay Routing Kyle Hogan, ..., and S. Devadas 2022 IEEE Symposium on Security and Privacy (SP) 2022 - 6 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

0.0

2024

[469] Individual Persistence Adaptation for User-Centric Evaluation of User Satisfaction in Recommender Systems Nozomu Onodera, ..., and M. Haseyama IEEE Access 2024 - 0 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

0.6

2019

[470] RLCache: Automated Cache Management Using Reinforcement Learning Sami Alabed ArXiv 2019 - 3 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

0.0

2023

[471] Modeling Trust and Reliance with Wait Time in a Human-Robot Interaction A. Maehigashi and S. Yamada ArXiv 2023 - 0 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

18.9

2018

[472] µTune: Auto-Tuned Threading for OLDI Microservices Akshitha Sriraman and T. Wenisch USENIX Symposium on Operating Systems Design and Implementation 2018 - 112 citations - Show abstract - Cite 0.1% topic match

0.1%

39.0

2008

[473] Rank-biased precision for measurement of retrieval effectiveness Alistair Moffat and J. Zobel ACM Trans. Inf. Syst. 2008 - 615 citations - Show abstract - Cite 0.1% topic match

0.1%

2.1

2016

[474] Adaptive Effort for Search Evaluation Metrics Jiepu Jiang and James Allan European Conference on Information Retrieval 2016 - 18 citations - Show abstract - Cite 0.1% topic match

0.1%

6.8

2000

[475] Don't keep your Internet customers waiting too long at the (virtual) front door B. Weinberg Journal of Interactive Marketing 2000 - 163 citations - Show abstract - Cite Abstract: One of the primary e-commerce challenges on the World Wide Web is when users experience intolerably long waits for a website's homepage to load. Zona Research, Inc. estimates that over $4 billion in lost revenue is due to slow downloads over the Internet. When the loading time of a homepage exceeds the maximum amount of time that a Web user is willing to wait, a Web user will either redirect the web-browser to an alternative (e.g., competitor's) website or quit using the Web; an opportunity, at the moment and perhaps forever, is lost to not only serve, influence, or interact with, a potential customer, but also to advance the growth of e-commerce. Given the important role of a homepage as a portal to a website or to a host of websites, it is critical that a homepage design consider not only appearance and functionality, but also loading time. The Internet industry has been devoting significant attention to solving the waiting time problem with approaches that are technical or operational in nature, with those most promising being extremely expensive and time consuming to employ (e.g., fiber optic cable). These approaches have not, up to this point in time, yielded the desired results. This research describes a complementary marketing approach to reducing the negative impact of the waiting time problem; one that is based on the psychological theorizing of “anchoring and adjustment,” with implications that would be relatively inexpensive to implement. In experiments where all Web users experienced the same actual wait for a homepage to load, those exposed to a shorter waiting time anchor, both perceived as shorter the waiting time for, and evaluated as higher the quality of, a homepage; and when the waiting time anchor was less than the actual waiting time, the perceived waiting time was less than the actual waiting time. In addition, those exposed to the smaller waiting time anchor were more likely to continue searching the associated website as opposed to searching a different website. 0.1% topic match

0.1%

8.6

2018

[476] Efficient Query Processing for Scalable Web Search N. Tonellotto, ..., and I. Ounis Found. Trends Inf. Retr. 2018 - 49 citations - Show abstract - Cite - PDF Abstract: Search engines are exceptionally important tools for accessing information in today’s world. In satisfying the information needs of millions of users, the effectiveness (the quality of the search results) and the efficiency (the speed at which the results are returned to the users) of a search engine are two goals that form a natural trade-off, as techniques that improve the effectiveness of the search engine can also make it less efficient. Meanwhile, search engines continue to rapidly evolve, with larger indexes, more complex retrieval strategies and growing query volumes. Hence, there is a need for the development of efficient query processing infrastructures that make appropriate sacrifices in effectiveness in order to make gains in efficiency. This survey comprehensively reviews the foundations of search engines, from index layouts to basic term-at-a-time (TAAT) and document-at-a-time (DAAT) query processing strategies, while also providing the latest trends in the literature in efficient query processing, including the coherent and systematic reviews of techniques such as dynamic pruning and impact-sorted posting lists as well as their variants and optimisations. Our explanations of query processing strategies, for instance the WAND and BMW dynamic pruning algorithms, are presented with illustrative figures showing how the processing state changes as the algorithms progress. Moreover, acknowledging the recent trends in applying a cascading infrastructure within search systems, this survey describes techniques for efficiently integrating effective learned models, such as those obtained from learning-torank techniques. The survey also covers the selective application of query processing techniques, often achieved by predicting the response times of the search engine (known as query efficiency prediction), and making per-query tradeoffs between efficiency and effectiveness to ensure that the required retrieval speed targets can be met. Finally, the survey concludes with a summary of open directions in efficient search infrastructures, namely the use of signatures, real-time, energy-efficient and modern hardware & software architectures. 0.1% topic match

0.1%

0.6

2021

[477] A novel classification model of collective user web behaviour based on network traffic contents Hongri Liu, ..., and Bailing Wang IET Networks 2021 - 2 citations - Show abstract - Cite 0.1% topic match

0.1%

80.8

1995

[479] IBM computer usability satisfaction questionnaires: Psychometric evaluation and instructions for use James R. Lewis Int. J. Hum. Comput. Interact. 1995 - 2395 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

12.0

2017

[480] Improving User Perceived Page Load Times Using Gaze Conor Kelton, ..., and Samir R Das Symposium on Networked Systems Design and Implementation 2017 - 92 citations - Show abstract - Cite 0.1% topic match

0.1%

0.0

2020

[481] Essential Issues to Consider for a Manufacturing Data Query System Based on Graph Lise Kim, ..., and Victor Fau Lecture Notes in Mechanical Engineering 2020 - 0 citations - Show abstract - Cite - PDF 0.1% topic match

0.1%

1.8

2015

[482] The Impact of Query Interface Design on Stress, Workload and Performance A. Edwards, ..., and L. Azzopardi European Conference on Information Retrieval 2015 - 17 citations - Show abstract - Cite 0.1% topic match

0.1%

0.4

2018

[483] APONE: Academic Platform for ONline Experiments M. Marrero Biennial Conference on Design of Experimental Search & Information Retrieval Systems 2018 - 3 citations - Show abstract - Cite 0.1% topic match

0.0%

2.9

2016

[484] On Obtaining Effort Based Judgements for Information Retrieval Manisha Verma, ..., and Nick Craswell Proceedings of the Ninth ACM International Conference on Web Search and Data Mining 2016 - 25 citations - Show abstract - Cite 0.0% topic match

0.0%

0.1

2013

[485] Search Costs in Consumer Product Choice: Does Delaying the Provision of Information Increase Choice Efficiency? Axel Sonntag ERN: Search 2013 - 1 citations - Show abstract - Cite - PDF 0.0% topic match

0.0%

12.3

2017

[486] The Positive and Negative Influence of Search Results on People's Decisions about the Efficacy of Medical Treatments Frances A. Pogacar, ..., and C. Clarke Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval 2017 - 85 citations - Show abstract - Cite - PDF 0.0% topic match

0.0%

1.0

2013

[488] Taking Our Sweet Time to Search M. Dörk, ..., and Rosamund Davies Journal Not Provided 2013 - 12 citations - Show abstract - Cite 0.0% topic match

0.0%

38.0

2011

[489] Measuring the quality of experience of HTTP video streaming Ricky K. P. Mok, ..., and R. Chang 12th IFIP/IEEE International Symposium on Integrated Network Management (IM 2011) and Workshops 2011 - 505 citations - Show abstract - Cite 0.0% topic match

0.0%

1.2

2016

[490] How to define the user's tolerance of response time in using mobile applications R. Zhou, ..., and L. Zhou 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) 2016 - 9 citations - Show abstract - Cite 0.0% topic match

0.0%

1.5

2021

[491] Airphant: Cloud-oriented Document Indexing Supawit Chockchowwat, ..., and Yongjoo Park 2022 IEEE 38th International Conference on Data Engineering (ICDE) 2021 - 4 citations - Show abstract - Cite - PDF 0.0% topic match

0.0%

8.9

2010

[492] Search behaviors in different task types Jingjing Liu, ..., and Xiangmin Zhang ACM/IEEE Joint Conference on Digital Libraries 2010 - 127 citations - Show abstract - Cite - PDF 0.0% topic match

0.0%

1.5

2017

[493] Perceptions of the Effect of Fragmented Attention on Mobile Web Search Tasks Morgan Harvey and Matthew Pointon Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval 2017 - 11 citations - Show abstract - Cite - PDF 0.0% topic match

0.0%

8.1

2007

[494] The influence of caption features on clickthrough patterns in web search C. Clarke, ..., and Ryen W. White Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007 - 138 citations - Show abstract - Cite 0.0% topic match

0.0%

0.3

2015

[495] On Human Information Processing in Information Retrieval ( Position Paper ) Alexandre Pereda-Baños and Ioannis Arapakis Journal Not Provided 2015 - 3 citations - Show abstract - Cite 0.0% topic match

0.0%

2.7

2019

[498] Enterprise search and discovery capability: The factors and generative mechanisms for user satisfaction P. Cleverley and Simon M. Burnett Journal of Information Science 2019 - 15 citations - Show abstract - Cite - PDF 0.0% topic match

0.0%

21.2

2008

[499] How does clickthrough data reflect retrieval quality? Filip Radlinski, ..., and T. Joachims International Conference on Information and Knowledge Management 2008 - 337 citations - Show abstract - Cite - PDF 0.0% topic match

0.0%

2.3

2017

[501] Validating simulated interaction for retrieval evaluation T. Pääkkönen, ..., and K. Järvelin Information Retrieval Journal 2017 - 16 citations - Show abstract - Cite 0.0% topic match

0.0%

1.8

2019

[502] Impact of response latency on sponsored search Xiao Bai and B. B. Cambazoglu Inf. Process. Manag. 2019 - 10 citations - Show abstract - Cite 0.0% topic match

0.0%

0.5

2020

[503] Towards adding verifiability to web-based Git repositories Hammad Afzali, ..., and Justin Cappos J. Comput. Secur. 2020 - 2 citations - Show abstract - Cite 0.0% topic match

0.0%

4.7

2017

[504] Searching on the Go: The Effects of Fragmented Attention on Mobile Web Search Tasks Morgan Harvey and Matthew Pointon Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval 2017 - 33 citations - Show abstract - Cite - PDF 0.0% topic match

0.0%

0.7

2017

[505] Towards Establishing Design Principles for Balancing Usability and Maintaining Cognitive Abilities G. Balasubramanian, ..., and Wai Keet Yong Interacción 2017 - 5 citations - Show abstract - Cite 0.0% topic match

0.0%

8.3

2014

[506] The Role of Search Result Position and Source Trustworthiness in the Selection of Web Search Results When Using a List or a Grid Interface Yvonne Kammerer and Peter Gerjets International Journal of Human–Computer Interaction 2014 - 88 citations - Show abstract - Cite 0.0% topic match

0.0%

1.4

2007

[507] How Fast Is Fast Enough K. Henke Technology and Learning 2007 - 24 citations - Show abstract - Cite 0.0% topic match

0.0%

0.0

2022

[508] This is not the End: Rethinking Serverless Function Termination Kalev Alpernas, ..., and Shmuel Sagiv ArXiv 2022 - 0 citations - Show abstract - Cite - PDF 0.0% topic match

0.0%

2.9

2020

[509] Users' Knowledge Use and Change during Information Searching Process: A Perspective of Vocabulary Usage Yao Zhang and Chang Liu Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020 2020 - 12 citations - Show abstract - Cite 0.0% topic match

0.0%

13.1

2019

[510] 150 Successful Machine Learning Models: 6 Lessons Learned at Booking.com Lucas Bernardi, ..., and PabloA . Estevez Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2019 - 67 citations - Show abstract - Cite 0.0% topic match

0.0%

6.2

2015

[512] Searching and Stopping: An Analysis of Stopping Rules and Strategies David Maxwell, ..., and Heikki Keskustalo Proceedings of the 24th ACM International on Conference on Information and Knowledge Management 2015 - 55 citations - Show abstract - Cite - PDF 0.0% topic match

0.0%

1.0

2005

[513] Funology M. Blythe, ..., and S. Wensveen https://doi.org/10.1007/1-4020-2967-5 2005 - 20 citations - Show abstract - Cite 0.0% topic match

0.0%

None

[514] Designing Equitable Data Center Scheduling Systems Sahana Rangarajan, ..., and Akshitha Sriraman Journal Not Provided None - 0 citations - Show abstract - Cite 0.0% topic match

0.0%

0.0

2024

[515] Is Interpretable Machine Learning Effective at Feature Selection for Neural Learning-to-Rank? Lijun Lyu, ..., and Avishek Anand ArXiv 2024 - 0 citations - Show abstract - Cite - PDF 0.0% topic match

0.0%

4.1

2017

[517] Engaged or Frustrated?: Disambiguating Emotional State in Search A. Edwards and D. Kelly Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval 2017 - 29 citations - Show abstract - Cite Abstract: One of the primary ways researchers have characterized engagement during information search is by increases in search behaviors, such as queries and clicks. However, studies have shown that frustration is also characterized by increases in these same behaviors. This research examines the differences in the search behaviors and physiologies of people who are engaged or frustrated during search. A 2x2 within-subject laboratory experiment was conducted with 40 participants. Engagement was induced by manipulating task interest and frustration was induced by manipulating the quality of the search results. Participants' interactions and physiological responses were recorded, and after they searched, they evaluated their levels of engagement, frustration and stress. Participants reported significantly greater levels of engagement when completing tasks that interested them and significantly less engagement during searches with poor results quality. For all search behaviors measured, only two significant differences were found according to task interest: participants had more scrolls and longer query intervals when searching for interesting tasks, suggesting greater interaction with content. Significant differences were found for nine behaviors according to results quality, including queries issued, number of SERPs displayed and number of SERP clicks, suggesting these are potentially better indicators of frustration rather than engagement. When presented with poor quality results, participants had significantly higher heart rates than when presented with normal quality results. Finally, participants had lower heart rates and greater skin conductance responses when conducting interesting tasks than when conducting uninteresting tasks. This research provides insight into the differences in search behaviors and physiologies of participants when they are engaged versus frustrated and presents techniques that can be used by those wishing to induce engagement and frustration during laboratory IIR studies. 0.0% topic match

0.0%

2.9

2020

[518] Towards Search Strategies for Better Privacy and Information Steven Zimmerman, ..., and Udo Kruschwitz Proceedings of the 2020 Conference on Human Information Interaction and Retrieval 2020 - 13 citations - Show abstract - Cite 0.0% topic match

0.0%

24.8

2015

[519] Opprentice: Towards Practical and Automatic Anomaly Detection Through Machine Learning Dapeng Liu, ..., and Mei Feng Proceedings of the 2015 Internet Measurement Conference 2015 - 220 citations - Show abstract - Cite 0.0% topic match

0.0%

6.8

2019

[520] Lowering the Latency of Data Processing Pipelines Through FPGA based Hardware Acceleration Muhsen Owaida, ..., and Pierre-Etienne Melet Proc. VLDB Endow. 2019 - 34 citations - Show abstract - Cite - PDF 0.0% topic match

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