Applying information foraging theory to understand user interaction with content-based image retrieval
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AbstractThe 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.
CitationLiu, 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
TypeConference papers, meetings and proceedings