標題: | Marketing segmentation using support vector clustering |
作者: | Huang, Jih-Jeng Tzeng, Gwo-Hshiung ong, Chorng-Shy Ong 科技管理研究所 Institute of Management of Technology |
關鍵字: | marketing segmentation;clustering algorithms;support vector clustering (SVC);k-means;self-organizing feature map (SOFM) |
公開日期: | 1-Feb-2007 |
摘要: | 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 |
期刊: | EXPERT SYSTEMS WITH APPLICATIONS |
Volume: | 32 |
Issue: | 2 |
起始頁: | 313 |
結束頁: | 317 |
Appears in Collections: | Articles |
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