Liu, Haiming, Mulholland, Paul, Song, Dawei, Uren, Victoria and Rüger, Stefan
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.
ACM, New York, NY, USA, pp. 135-144.
Official URL: http://doi.acm.org/10.1145/1840784.1840805
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.
|Item Type:||Book Section|
© 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 (2012) http://doi.acm.org/10.1145/1840784.1840805.|
|Uncontrolled Keywords (separate with ;):||content-based image retrieval; exploratory search; information foraging theory; user interaction; user modelling|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Schools:||School of Computing Engineering & Physcial Sciences|
|Deposited On:||01 Nov 2012 10:54|
|Last Modified:||01 Nov 2012 10:54|
Repository Staff Only: item control page