Marketing segmentation using support vector clustering
| dc.citation.epage | 317 | en_US |
| dc.citation.issue | 2 | en_US |
| dc.citation.spage | 313 | en_US |
| dc.citation.volume | 32 | en_US |
| dc.citation.woscount | 25 | |
| dc.contributor.author | Huang, Jih-Jeng | en_US |
| dc.contributor.author | Tzeng, Gwo-Hshiung | en_US |
| dc.contributor.author | ong, Chorng-Shy Ong | en_US |
| dc.contributor.department | 科技管理研究所 | zh_TW |
| dc.contributor.department | Institute of Management of Technology | en_US |
| dc.date.accessioned | 2014-12-08T15:14:47Z | |
| dc.date.available | 2014-12-08T15:14:47Z | |
| dc.date.issued | 2007-02-01 | en_US |
| dc.description.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. | en_US |
| dc.identifier.doi | 10.1016/j.eswa.2005.11.028 | en_US |
| dc.identifier.issn | 0957-4174 | en_US |
| dc.identifier.journal | EXPERT SYSTEMS WITH APPLICATIONS | en_US |
| dc.identifier.uri | http://dx.doi.org/10.1016/j.eswa.2005.11.028 | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/11172 | |
| dc.identifier.wosnumber | WOS:000242979100005 | |
| dc.language.iso | en_US | en_US |
| dc.subject | marketing segmentation | en_US |
| dc.subject | clustering algorithms | en_US |
| dc.subject | support vector clustering (SVC) | en_US |
| dc.subject | k-means | en_US |
| dc.subject | self-organizing feature map (SOFM) | en_US |
| dc.title | Marketing segmentation using support vector clustering | en_US |
| dc.type | Article | en_US |