Molecular dynamics-like data clustering approach

被引:13
|
作者
Li Junlin [1 ]
Fu Hongguang [1 ]
机构
[1] Univ Elect Sci & Technol China, Sch Comp Sci & Engn, Chengdu 610054, Peoples R China
关键词
Molecular dynamics; Dynamics clustering; Data mining; Data clustering; K-MEANS;
D O I
10.1016/j.patcog.2011.01.008
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Based on the molecular kinetic theory, a molecular dynamics-like data clustering approach is proposed in this paper. Clusters are extracted after data points fuse in the iterating space by the dynamical mechanism that is similar to the interacting mechanism between molecules through molecular forces. This approach is to find possible natural clusters without pre-specifying the number of clusters. Compared with 3 other clustering methods (trimmed k-means, JP algorithm and another gravitational model based method), this approach found clusters better than the other 3 methods in the experiments. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1721 / 1737
页数:17
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