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Encyclopedia of Database Systems pp 4646–4650Cite 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

    Cheng Xiang Zhai

Authors
  1. Hui Fang
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  2. Cheng Xiang Zhai
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Corresponding author

Correspondence to Hui Fang .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. Google Research, New York, NY, USA

    Cong Yu

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Fang, H., Zhai, C.X. (2018). Web Search Relevance Feedback. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_462

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