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

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    Authors
    Liu, Haiming
    Mulholland, Paul
    Song, Dawei
    Uren, Victoria
    Rüger, Stefan
    Issue Date
    2010
    
    Metadata
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    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.
    Citation
    Liu, H., Mulholland, P, Song, D., Uren, V. and Rüger, S. (2010) 'Applying information foraging theory to understand user interaction with content-based image retrieval', IIiX '10 Proceedings of the third symposium on Information interaction in context, pp. 135-144
    Publisher
    ACM
    URI
    http://hdl.handle.net/10547/297889
    DOI
    10.1145/1840784.1840805
    Additional Links
    http://portal.acm.org/citation.cfm?doid=1840784.1840805
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISBN
    9781450302470
    ae974a485f413a2113503eed53cd6c53
    10.1145/1840784.1840805
    Scopus Count
    Collections
    Centre for Research in Distributed Technologies (CREDIT)

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