Knowledge reduction based on asymmetrical similar matrix

doi:10.3778/j.issn.1002-8331.2010.07.013

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (7): 44-45.DOI: 10.3778/j.issn.1002-8331.2010.07.013

• 研究、探讨 • Previous Articles Next Articles

Knowledge reduction based on asymmetrical similar matrix

WANG Jia-yang¹，DUKUZUMUREMYI Jean Pau¹，HU Pei¹，GAO Can²

1.College of Information Science and Engineering，Central South University，Changsha 410083，China
2.Department of Computer Science and Technology，Tongji University，Shanghai 200092，China

Received:2008-09-23 Revised:2008-12-01 Online:2010-03-01 Published:2010-03-01
Contact: WANG Jia-yang

基于非对称相似差别矩阵知识约简

王加阳¹，杜库¹，胡沛¹，高灿²

1.中南大学信息科学与工程学院，长沙 410083
2.同济大学计算机科学与技术，上海 200092

通讯作者: 王加阳

Abstract

Abstract: In many kinds of information systems，there exists a situation where a value of data is null and algorithms given in many papers to calculate its optimal reduction have a high space complexity which is a big problem.To solve this problem，the equivalence relation of rough set theory is replaced by an asymmetrical similar relation，and from this relation，an asymmetrical similar matrix is defined，then a new heuristic algorithm with less space complexity that require core and knowledge reduction based on asymmetrical similar matrix is proposed，and an example is given to confirm the validity of the algorithm.

Key words: rough set, asymmetrical similarity matrix, discernibility matrix, knowledge reduction

摘要： 信息系统中存在着大量数据值缺省的情况，为寻求约简的最优解需耗费大量的时间。用非对称相似关系代替粗糙集理论中的等价关系，定义了非对称相似差别矩阵，提出了基于非对称相似差别矩阵的高效求核和知识约简算法。该算法无需改变初始不完备信息系统的结构，能直接处理缺省数据。实验结果表明，新算法所获得的决策规则简洁、高效，与缺省值无关。

关键词: 粗糙集, 非对称相似关系, 差别矩阵, 知识约简

CLC Number:

TP18

WANG Jia-yang¹，DUKUZUMUREMYI Jean Pau¹，HU Pei¹，GAO Can². Knowledge reduction based on asymmetrical similar matrix[J]. Computer Engineering and Applications, 2010, 46(7): 44-45.

王加阳¹，杜库¹，胡沛¹，高灿². 基于非对称相似差别矩阵知识约简[J]. 计算机工程与应用, 2010, 46(7): 44-45.

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Knowledge reduction based on asymmetrical similar matrix

基于非对称相似差别矩阵知识约简

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