A mathematical model of similarity and clustering

被引:0
|
作者
Sun, FS [1 ]
Tzeng, CH [1 ]
机构
[1] Ball State Univ, Dept Comp Sci, Muncie, IN 47306 USA
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper introduces an abstract model of data similarity and clustering. A similarity on a space Q is formulated explicitly by a reflexive and symmetric binary relation, called a tolerance relation, for which we introduce three types of coverings of Q. Given a covering U, a clustering is defined to be a minimal sub-covering. To search for an optimal clustering is to minimize the number of clusters, which is intractable in general. This paper proposes a heuristic method to search for sub-optimal clusterings for a given tolerance relation.
引用
收藏
页码:460 / 464
页数:5
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