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Research of CBR retrieval method based on rough set theory

机译:基于粗糙集理论的CBR检索方法研究

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Case retrieval is the key technology of case-based reasoning (CBR), directly affect the efficiency and quality of CBR. For the measurement issues of similar cases, using rough set theory to determine the importance of attributes and to distribute the rational weights of each property. Taking the improved nearest neighbor method which is based on the combination of Hamming distance and Euclidean distance to solve case similarity, improve the accuracy and efficiency of case matching.
机译:案例检索是基于案例的推理(CBR)的关键技术,直接影响到CBR的效率和质量。对于相似案例的度量问题,使用粗糙集理论确定属性的重要性并分配每个属性的合理权重。采用改进的基于汉明距离和欧氏距离相结合的最近邻方法来解决案例相似性,提高案例匹配的准确性和效率。

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