Article

Understanding user goals in web search

Authors:

Daniel E. Rose,

Danny LevinsonAuthors Info & Claims

WWW '04: Proceedings of the 13th international conference on World Wide Web

Pages 13 - 19

https://doi.org/10.1145/988672.988675

Published: 17 May 2004 Publication History

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Abstract

Previous work on understanding user web search behavior has focused on how people search and what they are searching for, but not why they are searching. In this paper, we describe a framework for understanding the underlying goals of user searches, and our experience in using the framework to manually classify queries from a web search engine. Our analysis suggests that so-called navigational" searches are less prevalent than generally believed while a previously unexplored "resource-seeking" goal may account for a large fraction of web searches. We also illustrate how this knowledge of user search goals might be used to improve future web search engines.

References

[1]

AltaVista, http://www.altavista.com.

Google Scholar

[2]

AltaVista, description of Prisma query refinement tool, http://www.altavista.com/help/search/pp.

Google Scholar

[3]

Anick, P. Using Terminological Feedback for Web Search Refinement: A Log-Based Study. Proceedings of SIGIR 2003, 88--95.

Digital Library

Google Scholar

[4]

Bates, M. J. Information Search Tactics. Journal of the American Society for Information Science, 30, July 1979, 205--214.

Crossref

Google Scholar

[5]

Bates, M. J. The Design of Browsing and Berrypicking Techniques for the Online Search Interface. Online Review 13, October 1989, 407--424.

Google Scholar

[6]

Belkin, N. J., Oddy, R. N., and Brooks, H. M. ASK for Information Retrieval: Part II. Results of a Design Study. Journal of Documentation, 38(3), Sep. 1982, 145--164.

Crossref

Google Scholar

[7]

Broder, A. A Taxonomy of Web Search. SIGIR Forum 36(2), 2002.

Digital Library

Google Scholar

[8]

Google, Description of "I'm Feeling Lucky" feature, http://www.google.com/help/features.html#lucky.

Google Scholar

[9]

Jansen, B. J. and Pooch, U. A Review of Web Searching Studies and a Framework for Future Research. Journal of the American Society of Information Science and Technology, 52(3), 235--246, 2000.

Digital Library

Google Scholar

[10]

Rose, D. E. Reconciling Information-Seeking Behavior with Search User Interfaces for the Web. Journal of the American Society of Information Science and Technology, to appear.

Digital Library

Google Scholar

[11]

Silverstein, C., Henzinger, M., Marais, H., and Moricz, M. Analysis of a Very Large Web Search Engine Query Log. SIGIR Forum, 33(3), 1999. Originally published as DEC Systems Research Center Technical Note, 1998.

Digital Library

Google Scholar

[12]

Sherman, C. and Sullivan, D. The Search Engine 'Perfect Page' Test. Search Day 391 (Nov. 4, 2002), http://www.searchenginewatch.com/searchday/02/sd1104-pptest.html.

Google Scholar

[13]

Spink, A., Jansen, B. J., Wolfram, D., and Saracevic, T. From E-Sex to E-Commerce: Web Search Changes. IEEE Computer, 35(3), 107--109, 2002.

Digital Library

Google Scholar

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https://dl.acm.org/doi/10.1145/3637528.3671647
Kong HYadav SLowy RRuzinov DKim J(2024)Understanding Online Job and Housing Search Practices of Neurodiverse Young Adults to Support Their IndependenceProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642578(1-14)Online publication date: 11-May-2024
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Juneja PZhang WSmith-Renner ALamba HTetreault JJaimes A(2024)Dissecting users' needs for search result explanationsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642059(1-17)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642059
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Index Terms

Understanding user goals in web search
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing

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Published In

WWW '04: Proceedings of the 13th international conference on World Wide Web

May 2004

754 pages

ISBN:158113844X

DOI:10.1145/988672

Conference Chairs:
Stuart Feldman
IBM Research
,
Mike Uretsky
New York University
,
Program Chairs:
Marc Najork
Microsoft Research
,
Craig Wills
Worcester Polytechnic Institute

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: 17 May 2004

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WWW04

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WWW04: The 2004 World Wide Web Conference ( in conjunction with ACM Conference on Electronic Commerce [EC'04])

May 17 - 20, 2004

NY, New York, USA

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Wan MSafavi TJauhar SKim YCounts SNeville JSuri SShah CWhite RYang LAndersen RBuscher GJoshi DRangan NBaeza-Yates RBonchi F(2024)TnT-LLM: Text Mining at Scale with Large Language ModelsProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671647(5836-5847)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671647
Kong HYadav SLowy RRuzinov DKim J(2024)Understanding Online Job and Housing Search Practices of Neurodiverse Young Adults to Support Their IndependenceProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642578(1-14)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642578
Juneja PZhang WSmith-Renner ALamba HTetreault JJaimes A(2024)Dissecting users' needs for search result explanationsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642059(1-17)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642059
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