On-line clustering

被引：22
|
作者：
Bouguettaya, A [1 ]
机构：
[1] UNIV COLORADO,BOULDER,CO 80309
来源：
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING | 1996年 / 8卷 / 02期
关键词：
cluster analysis; data clustering; databases; object-oriented databases;
D O I：
10.1109/69.494170
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this study, we focus on the stability and behavior of three widely used clustering algorithms. Various correlation coefficients are computed to help us understand the sensitivity of object clustering. Surprisingly, the results indicate that there is almost no difference among any clustering approach. Furthermore, all methods appear to be near stable. These findings tend to show that the clustering algorithms are independent of the way objects are inherently clustered.
引用
收藏
页码：333 / 339
页数：7
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