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New Technology of Library and Information Service  2010, Vol. 26 Issue (7/8): 88-94    DOI: 10.11925/infotech.1003-3513.2010.07-08.16
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Application of a Modified K-means Clustering Algorithm Based on PSO in Customer Segmentation of Securities Industry
Li Ying  Wu Yuanyuan  Ning Fujin
(Business School,East China University of Science and Technology, Shanghai 200237,China)
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Abstract  

According to the deficiencies of K-means clustering,the paper proposes a modified clustering algorithm which uses SD and PSO algorithm, and achieves this integrated algorithm in Java. In the analysis, the authors take customer transaction data of a securities company in Shanghai as an example. By transforming the database into a form suitable for mining, the paper applies the modified clustering algorithm to cluster segmentation model, and the clustering results show that the improved clustering algorithm can get higher quality clustering results.

Key wordsPSO      K-means algorithm      Customer segmentation     
Received: 24 May 2010      Published: 19 September 2010
: 

F832 

 
  TP301.6

 
Corresponding Authors: Ning Fujin     E-mail: ningfujin@126.com
About author:: Li Ying Wu Yuanyuan Ning Fujin

Cite this article:

Li Ying Wu Yuanyuan Ning Fujin. Application of a Modified K-means Clustering Algorithm Based on PSO in Customer Segmentation of Securities Industry. New Technology of Library and Information Service, 2010, 26(7/8): 88-94.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2010.07-08.16     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2010/V26/I7/8/88

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