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Applying information foraging theory to understand user interaction with content-based image retrieval

  • Haiming Liu
    ,
  • Paul Mulholland
    ,
  • Dawei Song
    ,
  • Victoria Uren
    ,
  • Stefan Rüger
  • Open University Milton Keynes
    ,
  • Robert Gordon University
    ,
  • University of Sheffield
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

The paper proposes an ISE (Information goal, Search strategy, Evaluation threshold) user classification model based on Information Foraging Theory for understanding user interaction with content-based image retrieval (CBIR). The proposed model is verified by a multiple linear regression analysis based on 50 users' interaction features collected from a task-based user study of interactive CBIR systems. To our best knowledge, this is the first principled user classification model in CBIR verified by a formal and systematic qualitative analysis of extensive user interaction data.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Publication milestones

  • Published - 01/01/2010

Publication status

Published - 01/01/2010

Publisher

Association for Computing Machinery, United States

ISBN (Print)

9781450302470

ISBN (Electronic)

9781450302470

External Publication IDs

  • handle.net: 10547/297889
  • Scopus: 77957961245

Host publication title

nan

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