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. Thus, we propose a four-factor user interaction model and investigate its effects on CBIR by an empirical and a user evaluation. Whilst the model was developed for our research purposes, we believe the model could be adapted to any content-based search system.

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