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To exploit co-occurrence patterns among features and target semantics while keeping the simplicity of the keywordbased visual search, a novel reranking methods is proposed. The approach, ordinal reranking, reranks an initial search list by utilizing the co-occurrence patterns via the ranking functions such as ListNet. Ranking functions are by nature more effective than classification-based reranking methods in mining ordinal relationships. In addition, ordinal reranking is ease of the ad-hocdoi:10.1109/icme.2008.4607427 dblp:conf/icmcs/YangH08 fatcat:wjmbfhsr4zc4pevpxvlvdyqqmy