Title: Marketing segmentation using support vector clustering
Authors: Huang, Jih-Jeng
Tzeng, Gwo-Hshiung
ong, Chorng-Shy Ong
科技管理研究所
Institute of Management of Technology
Keywords: marketing segmentation;clustering algorithms;support vector clustering (SVC);k-means;self-organizing feature map (SOFM)
Issue Date: 1-Feb-2007
Abstract: Marketing segmentation is widely used for targeting a smaller market and is useful for decision makers to reach all customers effectively with one basic marketing mix. Although several clustering algorithms have been proposed to deal with marketing segmentation problems, a soundly method seems to be limited. In this paper, support vector clustering (SVC) is used for marketing segmentation. A case study of a drink company is used to demonstrate the proposed method and compared with the k-means and the self-organizing feature map (SOFM) methods. On the basis of the numerical results, we can conclude that SVC outperforms the other methods in marketing segmentation. (C) 2005 Published by Elsevier Ltd.
URI: http://dx.doi.org/10.1016/j.eswa.2005.11.028
http://hdl.handle.net/11536/11172
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2005.11.028
Journal: EXPERT SYSTEMS WITH APPLICATIONS
Volume: 32
Issue: 2
Begin Page: 313
End Page: 317
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