知识的划分粒度表示法<sup>*</sup>

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摘要对知识的分类能力给予量化，提出一种知识表示法——划分粒度表示法，利用划分粒度可定量表示知识的分类能力.首先给出粗糙集理论中主要概念的代数表示，其次定义知识的划分粒度并研究它的性质，最后证明知识的代数表示与划分粒度表示是等价的.

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	冯琴荣
	苗夺谦
	程昳
	徐菲菲

关键词 ：粗糙集, 信息系统, 划分粒度, 知识约简

Abstract：A quantitative representation for the classification ability of knowledge is described, and a representation for knowledge is given. Firstly, the algebraic representation of main concepts in rough sets is presented. Next, the concept of partition granularity is defined, and its properties are analyzed. Finally, the equivalence between the algebraic representation of knowledge and partition granularity representation is proved.

Key words： Rough Set Information System Partition Granularity Knowledge Reduction

收稿日期: 2007-09-26

ZTFLH:

TP181

基金资助:国家自然科学基金(No.60475019, 60775036)、教育部博士点专项基金(No.20060247039)资助项目

作者简介: 冯琴荣，女，1972年生，副教授，博士研究生，主要研究方向为粗糙集理论、粒度计算、数据挖掘.E-mail: fengqr72@163.com.苗夺谦，男，1964年生，教授，博士生导师，主要研究方向为人工智能、模式识别、数据挖掘、粗糙集理论.程昳，女，1977年生，博士研究生，主要研究方向为粗糙集理论、模糊粗糙集理论及应用.徐菲菲，女，1983年生，博士研究生，主要研究方向为模糊粗糙集理论、粒度计算.

引用本文:

冯琴荣，苗夺谦，程昳，徐菲菲. 知识的划分粒度表示法^*[J]. 模式识别与人工智能, 2009, 22(1): 65-69. FENG Qin-Rong, MIAO Duo-Qian,CHENG Yi, XU Fei-Fei. Knowledge Representation Using Partition Granularity. , 2009, 22(1): 65-69.

链接本文:

http://manu46.magtech.com.cn/Jweb_prai/CN/ 或 http://manu46.magtech.com.cn/Jweb_prai/CN/Y2009/V22/I1/65

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