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Encyclopedia of Database Systems pp 3493–3497Cite as

Web Search Relevance Feedback

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Definition

Relevance feedback refers to an interactive cycle that helps to improve the retrieval performance based on the relevance judgments provided by a user. Specifically, when a user issues a query to describe an information need, an information retrieval system would first return a set of initial results and then ask the user to judge whether some information items (typically documents or passages) are relevant or not. After that, the system would reformulate the query based on the collected feedback information, and return a set of retrieval results, which presumably would be better than the initial retrieval results. This procedure could be repeated.

Historical Background

Quality of retrieval results highly depends on how effective a user’s query (usually a set of keywords) is in distinguishing relevant documents from non-relevant ones. Ideally, the keywords used in the query should occur only in the relevant documents and not in any non-relevant document. Unfortunately, in...

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Recommended Reading

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Author information

Authors and Affiliations

  1. University of Delaware, Newark, DE, USA

    Hui Fang

  2. University of Illinois at Urbana-Champaign, Urbana, IL, USA

    ChengXiang Zhai

Authors
  1. Hui Fang
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  2. ChengXiang Zhai
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Editor information

Editors and Affiliations

  1. Professor, College of Computing, Georgia Institute of Technology, 266 Ferst Drive, 30332-0765, Atlanta, GA, USA

    LING LIU

  2. Professor and Director, University Research Chair, Database Research Group David R. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    M. TAMER ÖZSU

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Fang, H., Zhai, C. (2009). Web Search Relevance Feedback. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_462

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