DIVISIVE CLUSTERING OF SYMBOLIC OBJECTS USING THE CONCEPTS OF BOTH SIMILARITY AND DISSIMILARITY

被引：60

作者：

GOWDA, KC

RAVI, TV

机构：

[1] Department of Computer Science and Engineering, S. J. College of Engineering, Mysore

来源：

PATTERN RECOGNITION | 1995年 / 28卷 / 08期

关键词：

SYMBOLIC CLUSTERING; SYMBOLIC SIMILARITY; SYMBOLIC-DISSIMILARITY; MINIMUM SPANNING TREE; INCONSISTENT EDGE;

D O I：

10.1016/0031-3203(95)00003-I

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A new approach to clustering of symbolic objects which makes use of both similarity and dissimilarity measures is proposed. The proposed modified new similarity and dissimilarity measures will take into consideration the position, span and content of symbolic objects. The similarity and dissimilarity measures used are of new type. The advantages of the proposed modified measures are presented. A divisive clustering algorithm which makes use of both similarity and dissimilarity is proposed. The results obtained by the proposed method is compared with other methods.

引用

页码：1277 / 1282

页数：6

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GOWDA, KC ;

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[10] SYMBOLIC CLUSTERING USING A NEW DISSIMILARITY MEASURE [J].

GOWDA, KC ;

DIDAY, E .

PATTERN RECOGNITION, 1991, 24 (06) :567-578

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