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Knowledge effects on document selection in search results pages

Authors:

Jacek GwizdkaAuthors Info & Claims

SIGIR '11: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval

Pages 1219 - 1220

https://doi.org/10.1145/2009916.2010128

Published: 24 July 2011 Publication History

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Abstract

Click through events in search results pages (SERPs) are not reliable implicit indicators of document relevance. A user's task and domain knowledge are key factors in recognition and link selection and the most useful SERP document links may be those that best match the user's domain knowledge. User study participants rated their knowledge of genomics MeSH terms before conducting 2004 TREC Genomics Track tasks. Each participant's document knowledge was represented by their knowledge of the indexing MeSH terms. Results show high, intermediate, and low domain knowledge groups had similar document selection SERP rank distributions. SERP link selection distribution varied when participant knowledge of the available documents was analyzed. High domain knowledge participants usually selected a document with the highest personal knowledge rating. Low domain knowledge participants were reasonably successful at selecting available documents of which they had the most knowledge, while intermediate knowledge participants often failed to do so. This evidence for knowledge effects on SERP link selection may contribute to understanding the potential for personalization of search results ranking based on user domain knowledge.

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Cited By

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Schultheiß S(2023)How search engine marketing influences user knowledge gainProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578297(475-478)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578297
Ghafourian YHanbury AKnoth P(2023)Ranking for Learning: Studying Users’ Perceptions of Relevance, Understandability, and EngagementLinking Theory and Practice of Digital Libraries10.1007/978-3-031-43849-3_25(284-291)Online publication date: 22-Sep-2023
https://doi.org/10.1007/978-3-031-43849-3_25
Palani SFourney AWilliams SLarson KSpiridonova IMorris MHuang JChang YCheng XKamps JMurdock VWen JLiu Y(2020)An Eye Tracking Study of Web Search by People With and Without DyslexiaProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401103(729-738)Online publication date: 25-Jul-2020
https://dl.acm.org/doi/10.1145/3397271.3401103
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Index Terms

Knowledge effects on document selection in search results pages
1. Information systems
  1. Information retrieval
    1. Evaluation of retrieval results
      1. Relevance assessment
    2. Information retrieval query processing

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Published In

SIGIR '11: Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval

July 2011

1374 pages

ISBN:9781450307574

DOI:10.1145/2009916

General Chairs:
Wei-Ying Ma
Microsoft Research Asia, China
,
Jian-Yun Nie
University of Montreal, Canada
,
Program Chairs:
Ricardo Baeza-Yates
Yahoo! Research, Spain
,
Tat-Seng Chua
National University of Singapore
,
W. Bruce Croft
University of Massachusetts, Amherst, USA

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 July 2011

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SIGIR '11

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SIGIR

SIGIR '11: The 34th International ACM SIGIR conference on research and development in Information Retrieval

July 24 - 28, 2011

Beijing, China

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

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Schultheiß S(2023)How search engine marketing influences user knowledge gainProceedings of the 2023 Conference on Human Information Interaction and Retrieval10.1145/3576840.3578297(475-478)Online publication date: 19-Mar-2023
https://dl.acm.org/doi/10.1145/3576840.3578297
Ghafourian YHanbury AKnoth P(2023)Ranking for Learning: Studying Users’ Perceptions of Relevance, Understandability, and EngagementLinking Theory and Practice of Digital Libraries10.1007/978-3-031-43849-3_25(284-291)Online publication date: 22-Sep-2023
https://doi.org/10.1007/978-3-031-43849-3_25
Palani SFourney AWilliams SLarson KSpiridonova IMorris MHuang JChang YCheng XKamps JMurdock VWen JLiu Y(2020)An Eye Tracking Study of Web Search by People With and Without DyslexiaProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401103(729-738)Online publication date: 25-Jul-2020
https://dl.acm.org/doi/10.1145/3397271.3401103
Karanam Svan Oostendorp H(2020)Cognitive Modeling of Age and Domain Knowledge Differences in Information SearchUnderstanding and Improving Information Search10.1007/978-3-030-38825-6_4(47-68)Online publication date: 30-May-2020
https://doi.org/10.1007/978-3-030-38825-6_4
Fu W(2020)How Cognitive Computational Models Can Improve Information SearchUnderstanding and Improving Information Search10.1007/978-3-030-38825-6_3(29-45)Online publication date: 30-May-2020
https://doi.org/10.1007/978-3-030-38825-6_3
Liu JZhang X(2019)The role of domain knowledge in document selection from search resultsJournal of the Association for Information Science and Technology10.1002/asi.2419970:11(1236-1247)Online publication date: 6-Oct-2019
https://dl.acm.org/doi/10.1002/asi.24199
Yamamoto TYamamoto YFujita SCuzzocrea AAllan JPaton NSrivastava DAgrawal RBroder AZaki MCandan SLabrinidis ASchuster AWang H(2018)Exploring People's Attitudes and Behaviors Toward Careful Information Seeking in Web SearchProceedings of the 27th ACM International Conference on Information and Knowledge Management10.1145/3269206.3271799(963-972)Online publication date: 17-Oct-2018
https://dl.acm.org/doi/10.1145/3269206.3271799
Yang LFang CJin HHoffman MEstrin D(2018)Characterizing User Skills from Application Usage Traces with Hierarchical Attention Recurrent NetworksACM Transactions on Intelligent Systems and Technology10.1145/32322319:6(1-18)Online publication date: 29-Oct-2018
https://dl.acm.org/doi/10.1145/3232231
Ruotsalo TPeltonen JEugster MGłowacka DFloréen PMyllymäki PJacucci GKaski S(2018)Interactive Intent Modeling for Exploratory SearchACM Transactions on Information Systems10.1145/323159336:4(1-46)Online publication date: 3-Oct-2018
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Mao JLiu YKando NZhang MMa S(2018)How Does Domain Expertise Affect Users’ Search Interaction and Outcome in Exploratory Search?ACM Transactions on Information Systems10.1145/322304536:4(1-30)Online publication date: 17-Jul-2018
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