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Encyclopedia of Database Systems pp 1384–1389Cite as

Image Retrieval and Relevance Feedback

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Definition

Relevance feedback is a means of refining a query in an information retrieval system by asking the user to specify how relevant each result of the query is. An image retrieval session relying on relevance feedback is interactive and iterative. The session is divided into several consecutive rounds. At every round, the user provides feedback regarding the current retrieval results, usually by qualifying the returned images as either “relevant” or “irrelevant”; from this feedback, the system attempts to better identify the target of the user and to return improved results. A relevance feedback mechanism must maximize the relevance of the results while minimizing the amount of interaction between the user and the system.

Historical Background

In the early years of content-based image retrieval (CBIR), query by visual example (QBVE) was a prevailing paradigm. To support QBVE, an image retrieval system must first extract, during an off-line phase, a description in terms of...

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Author information

Authors and Affiliations

  1. National Conservatory of Arts and Crafts, Paris, France

    Michel Crucianu

Authors
  1. Michel Crucianu
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Editor information

Editors and Affiliations

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

    LING LIU (Professor) (Professor)

  2. 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 (Professor and Director, University Research Chair) (Professor and Director, University Research Chair)

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© 2009 Springer Science+Business Media, LLC

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Crucianu, M. (2009). Image Retrieval and 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_1016

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