Applying Information Foraging Theory to understand user interaction with content-based image retrieval


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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Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > Aston Business School > Advanced Services Group
Additional Information: © ACM, 2010. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in IIiX '10 Proceedings of the third symposium on Information interaction in context,
Event Title: 2010 Information Interaction in Context Symposium
Event Type: Other
Event Dates: 2010-08-18 - 2010-08-21
ISBN: 978-1-4503-0247-0
Last Modified: 25 Jan 2024 08:23
Date Deposited: 21 Nov 2013 09:21
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2010-08-18
Authors: Liu, Haiming
Mulholland, Paul
Song, Dawei
Uren, Victoria (ORCID Profile 0000-0002-1303-5574)
Rüger, Stefan



Version: Accepted Version

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