A general incremental hierarchical clustering method

被引：0
|
作者：
He, L. L. [1 ]
Bai, H. T. [2 ]
Sun, J. G. [1 ]
Jin, C. Z. [1 ]
机构：
[1] Jilin Univ, Coll Comp Sci & Technol, Qianwei Rd 10, Changchun 130012, Peoples R China
[2] ShenZhen Telecom, New Technol Center, Shenzhen, Peoples R China
来源：
COMPUTATIONAL METHODS, PTS 1 AND 2 | 2006年
关键词：
hierarchical clustering method; ICHAMELEON; incremental method;
D O I：
10.1007/978-1-4020-3953-9_45
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Data mining, i.e., clustering analysis, is a challenging task due to the huge amounts of data. In this paper, we propose a general incremental hierarchical clustering method dealing with incremental data sets in data warehouse environment for data mining to reduce the cost further. As an example, we put forward ICHAMELEON, the improvement of CHAMELEON, which is a hierarchical clustering method, and demonstrate that ICHAMELEON is highly efficient in terms of time complexity. Experimental results on very large data sets are presented which show the efficiency of ICHAMELEON compared with CHAMELEON.
引用
收藏
页码：1303 / +
页数：2
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