Methods of Feature Weighting Calculation and Case Retrieval in CBR Case Base

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This article proposes the necessity and feasibility of the use of Data Mining and Knowledge Discovery in CBR reasoning. This paper focuses on the method of empowering feature items based on least squares method parameter identification, and achieve the method of Similarity case retrieval on this basis, the object is the typical case database of railway rescue. The simulation results show that: the least square method can effectively make estimation and identification of the feature parameters, and can continuously correct on-line. High accuracy and fast convergence characteristics of the assigned parameters show that the algorithm has a certain application value.

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1391-1398

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January 2014

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