National Changhua University of Education Institutional Repository : Item 987654321/17070
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 6507/11669
造访人次 : 30052030      在线人数 : 702
RC Version 3.2 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 进阶搜寻

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://ir.ncue.edu.tw/ir/handle/987654321/17070

题名: A Case Study of Applying Data Mining Techniques in An Outfitter's Customer Value Analysis
作者: Huang, Shian-Chang;Chang, En-Chi;Wu, Hsin-Hung
贡献者: 企業管理學系
关键词: K-means method;Fuzzy c-means method;Bagged clustering algorithm;Value analysis;Cluster quality assessment
日期: 2009-04
上传时间: 2013-07-11T09:04:29Z
出版者: Elsevier Ltd.
摘要: This study applies K-means method, fuzzy c-means clustering method and bagged clustering algorithm to the analysis of customer value for an outfitter in Taipei, Taiwan. These three techniques bear similar philosophy for data classification. Thus, it would be of interest to know which clustering technique performs best in a real world case of evaluating customer value. Using cluster quality assessment, this study concludes that bagged clustering algorithm outperforms the other two methods. To conclude the analyses, this study also suggests marketing strategies for each cluster based on the results generated by bagged clustering technique.
關聯: Expert Systems with Applications, 36(3): 5909-5915
显示于类别:[企業管理學系] 期刊論文

文件中的档案:

档案 大小格式浏览次数
index.html0KbHTML851检视/开启


在NCUEIR中所有的数据项都受到原著作权保护.

 

DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈