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Predictive modeling of first-click behavior in web-search

Published: 23 May 2006 Publication History

Abstract

Search engine results are usually presented in some form of text summary (e.g., document title, some snippets of the page's content, a URL, etc). Based on the information contained within these summaries users make relevance judgments about what links best suit their information needs. Current research suggests that these relevance judgments are in the service of some search strategy. In this paper, we model two different search strategies (the comparison and threshold strategies) and determine how well they fit data gathered from an experiment on user search within a simulated Google environment.

References

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Keane, M. T., O'Brien M. & Smyth B. (in press) Are people biased in their use of search-engines? Communications of the ACM.
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Cited By

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  • (2013)Report on the SIGIR 2013 workshop on modeling user behavior for information retrieval evaluation (MUBE 2013)ACM SIGIR Forum10.1145/2568388.256840347:2(84-95)Online publication date: 21-Jan-2013
  • (2012)Modeling user variance in time-biased gainProceedings of the Symposium on Human-Computer Interaction and Information Retrieval10.1145/2391224.2391227(1-10)Online publication date: 4-Oct-2012
  • (2007)Analysis of online video search and sharingProceedings of the eighteenth conference on Hypertext and hypermedia10.1145/1286240.1286301(217-226)Online publication date: 10-Sep-2007
  • Show More Cited By

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Published In

cover image ACM Conferences
WWW '06: Proceedings of the 15th international conference on World Wide Web
May 2006
1102 pages
ISBN:1595933239
DOI:10.1145/1135777
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 May 2006

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Author Tags

  1. empirical tests
  2. information navigation
  3. information scent
  4. link analysis
  5. predictive user modeling
  6. search behavior
  7. web evolution

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Cited By

View all
  • (2013)Report on the SIGIR 2013 workshop on modeling user behavior for information retrieval evaluation (MUBE 2013)ACM SIGIR Forum10.1145/2568388.256840347:2(84-95)Online publication date: 21-Jan-2013
  • (2012)Modeling user variance in time-biased gainProceedings of the Symposium on Human-Computer Interaction and Information Retrieval10.1145/2391224.2391227(1-10)Online publication date: 4-Oct-2012
  • (2007)Analysis of online video search and sharingProceedings of the eighteenth conference on Hypertext and hypermedia10.1145/1286240.1286301(217-226)Online publication date: 10-Sep-2007
  • (2007)Modeling user behavior using a search-engineProceedings of the 12th international conference on Intelligent user interfaces10.1145/1216295.1216366(357-360)Online publication date: 28-Jan-2007

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