An information foraging theory based user study of an adaptive user interaction framework for content-based image retrieval

Authors:
Haiming Liu;Paul Mulholland;Dawei Song;Victoria Uren;Stefan Rüger
Affiliations:
Knowledge Media Institute, The Open University, Milton Keynes, UK;Knowledge Media Institute, The Open University, Milton Keynes, UK;School of Computing, The Robert Gordon University, Aberdeen, UK;Department of Computer Science, University of Sheffield, Sheffield, UK;Knowledge Media Institute, The Open University, Milton Keynes, UK
Venue:
MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part II
Year:
2011

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Abstract

This paper presents the design and results of a task-based user study, based on Information Foraging Theory, on a novel user interaction framework - uInteract - for content-based image retrieval (CBIR). The framework includes a four-factor user interaction model and an interactive interface. The user study involves three focused evaluations, 12 simulated real life search tasks with different complexity levels, 12 comparative systems and 50 subjects. Information Foraging Theory is applied to the user study design and the quantitative data analysis. The systematic findings have not only shown how effective and easy to use the uInteract framework is, but also illustrate the value of Information Foraging Theory for interpreting user interaction with CBIR.