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. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Liu, H., Uren, V., Song, D., & Rüger, S. (2009). A four-factor user interaction model for content-based image retrieval. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5766 LNCS, pp. 297–304). https://doi.org/10.1007/978-3-642-04417-5_29
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