• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2010, Vol. 32 ›› Issue (10): 105-107.doi: 10.3969/j.issn.1007130X.2010.

• 论文 • Previous Articles     Next Articles

A KMeans Algorithm Based onthe Optimal Initial Clustering Center

WANG Saifang,DAI Fang,WANG Wanbin,ZHANG Xiaoyu   

  1. (School of Sciences,Xi’an University of Technology,Xi’an 710054,China)
  • Received:2009-06-24 Revised:2009-11-05 Online:2010-09-29 Published:2010-09-29

Abstract:

Traditional Kmeans clustering algorithms are sensitive to the selection of initial clustering centers and isolated points. Considering these problems, a new method based on the density of points is presented in this paper. First of all, we select initial clustering centers through the proposed method. Then, we apply a Kmeans clustering algorithm to cluster the data, and process the isolated points especially. The experimental results demonstrate that the proposed method can get better clustering results.

Key words: clustering;Kmeans clustering algorithm;density of points