Liu, Haiming; Uren, Victoria; Song, Dawei and Rüger, Stefan
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In order to bridge the 'Semantic gap', a number of relevance feedback (RF) mechanisms have been applied to content-based image retrieval (CBIR). However current RF techniques in most existing CBIR systems still lack satisfactory user interaction although some work has been done to improve the interaction as well as the search accuracy. In this paper, we propose a four-factor user interaction model and investigate its effects on CBIR by an empirical evaluation. Whilst the model was developed for our research purposes, we believe the model could be adapted to any content-based search system.
|Item Type:||Conference Item|
|Copyright Holders:||2009 Springer-Verlag|
|Keywords:||user interaction; relevance feedback; content-based image retrieval|
|Academic Unit/School:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
|Depositing User:||Colin Smith|
|Date Deposited:||15 Oct 2010 14:14|
|Last Modified:||29 Nov 2016 16:00|
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