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Liu, Haiming, Mulholland, Paul, Song, Dawei, Uren, Victoria and Rüger, Stefan (2010) Applying information foraging theory to understand user interaction with content-based image retrieval. In: IIiX '10 Proceedings of the third symposium on Information interaction in context. IIiX '10 . Association for Computing Machinery (ACM), New York, NY, USA, pp. 135-144. ISBN 978-1-4503-0247-0
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Official URL: http://doi.acm.org/10.1145/1840784.1840805
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.
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