An intelligent market segmentation system using k-means and particle swarm optimization

Authors:
Chui-Yu Chiu;Yi-Feng Chen;I-Ting Kuo;He Chun Ku
Affiliations:
Department of Industrial Engineering and Management, National Taipei University of Technology, 1, Section 3, Chung-Hsiao East Road, Taipei 106, Taiwan, ROC;Department of Industrial Engineering and Management, National Taipei University of Technology, 1, Section 3, Chung-Hsiao East Road, Taipei 106, Taiwan, ROC;Department of Industrial Engineering and Management, National Taipei University of Technology, 1, Section 3, Chung-Hsiao East Road, Taipei 106, Taiwan, ROC;Department of Industrial Engineering and Management, National Taipei University of Technology, 1, Section 3, Chung-Hsiao East Road, Taipei 106, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

With the development of information technology (IT), how to find useful information existed in vast data has become an important issue. The most broadly discussed technique is data mining, which has been successfully applied to many fields as analytic tool. Data mining extracts implicit, previously unknown, and potentially useful information from data. Clustering is one of the most important and useful technologies in data mining methods. Clustering is to group objects together, which is based on the difference of similarity on each object, and making highly homogeneity in the same cluster, or highly heterogeneity between each group. In this paper, we propose a market segmentation system based on the structure of decision support system which integrates conventional statistic analysis method and intelligent clustering methods such as artificial neural network, and particle swarm optimization methods. The proposed system is expected to provide precise market segmentation for marketing strategy decision making and extended application.