Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (34): 19-21.

• 博士论坛 • Previous Articles     Next Articles

Reduction algorithm for information systems based on knowledge partition granularity

FENG Qin-rong1,2,MIAO Duo-qian1,CHENG Yi1   

  1. 1.Department of Computer Science and Technology,Tongji University,Shanghai 201804,China
    2.College of Mathematics and Computer Science,Shanxi Normal University,Linfen,Shanxi 041004,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-12-01 Published:2007-12-01
  • Contact: FENG Qin-rong

基于知识划分粒度的信息系统约简算法

冯琴荣1,2,苗夺谦1,程 昳1   

  1. 1.同济大学 计算机科学与技术系,上海 201804
    2.山西师范大学 数学与计算机科学学院,山西 临汾 041004
  • 通讯作者: 冯琴荣

Abstract: Knowledge and classifications are related together by the theory of rough sets which claim that knowledge is deep-seated in the classificatory abilities of human beings.In this paper,quantitatively represent the ability of knowledge’s classification by partition granularity.Firstly,the relationship between knowledge and its partition granularity is set up.Secondly,the significance of attributes is defined from the view of partition granularity,and a heuristic algorithm based on partition granularity for reduction of an information system is proposed.Finally,shows that this algorithm is effective for dealing with relatively large-scale information system through an example.

Key words: rough sets, knowledge reduction, partition granularity, information systems

摘要: 粗糙集理论认为知识就是分类。对知识的分类能力给予了量化,提出利用知识的划分粒度来定量地表示知识的分类能力。首先建立了知识与其划分粒度间的关系;其次,基于划分粒度定义了属性的重要性,并以此为启发式信息设计了一个信息系统的约简算法;最后通过实例表明,该算法是高效的。

关键词: 粗糙集, 知识约简, 划分粒度, 信息系统