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In case-based reasoning (CBR), cases are generally represented by features. Different features have different importance, which are often described by weights. So how to adaptively learning weights of different features is a very key issue in CBR, which impact directly the quality and performance of case extraction. Currently, in most practical CBR systems, the feature weights are given by domain...