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    基于粗集理论的知识含量度量研究

    Research on Knowledge Capacity Measurement of Knowledge Base Based on Rough Set

    • 摘要: 知识库中知识含量度量是知识处理领域中的基础问题 现有的度量方式都是采用相对度量或信息熵的方式 ,度量结果具有相对性 ,并且不易体现知识本质在于分类的特性 根据知识库在结构上的差异程度 ,将知识库的相似性关系定义为等价、等构、等势 3种关系 在这 3种关系的基础上 ,提出了用于度量知识库中知识含量的测度所需要遵循的 4条准则 ,并基于此 4条准则对基于信息熵的度量Hent的正确性进行了证明 ,最后还提出了一种基于分类的度量方式Hdis 以上工作进一步深入描述了知识的本质及其度量方式的内涵 ,有助于人们在此基础上构造新的知识处理算法

       

      Abstract: In the classical rough set theory, d R(F) and r R(F) are used to describe the relative knowledge capacity of two knowledge base This description is relative and inexact In this paper,according to the difference degree of knowledge in structure, the similarity relation of knowledge base is defined as the equivalence, equal structure and equal potential relation Then, on the basis of the above three relations, the four criterions which define the measure of the knowledge capacity of knowledge base are proposed The meantime, two methods which measure the knowledge capacity of knowledge base are given and validated

       

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