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Two methods for retrieval relevance optimization using the user’s feedback is proposed for a content-based image retrieval (CBIR) system. First, the feature space used in database image clustering for coarse classification is transferred to a preference feature space according to the user’s feedback by a map generated by supervised training, thereby enabling to collect user-preferred images in the...