標題: Apply robust segmentation to the service industry using kernel induced fuzzy clustering techniques
作者: Wang, Chih-Hsuan
交大名義發表
工業工程與管理學系
National Chiao Tung University
Department of Industrial Engineering and Management
關鍵字: Robust classification;Robust segmentation;Kernel induced fuzzy clustering
公開日期: 1-十二月-2010
摘要: To understand customers' characteristics and their desire is critical for modern CRM (customer relationship management). The easiest way for a company to achieve this goal is to target their customers and then to serve them through providing a variety of personalized and satisfactory goods or service. In order to put the right products or services and allocate resources to specific targeted groups, many CRM researchers and/or practitioners attempt to provide a variety of ways for effective customer segmentation. Unfortunately, most existing approaches are vulnerable to outliers in practice and hence segmentation results may be unsatisfactory or seriously biased. In this study, a hybrid approach that incorporates kernel induced fuzzy clustering techniques is proposed to overcome the above-mentioned difficulties. Two real datasets, including the WINE and the RFM, are used to validate the proposed approach. Experimental results show that the proposed approach cannot only fulfill robust classification, but also achieve robust segmentation when applied to the noisy dataset. (C) 2010 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.eswa.2010.05.042
http://hdl.handle.net/11536/31872
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2010.05.042
期刊: EXPERT SYSTEMS WITH APPLICATIONS
Volume: 37
Issue: 12
起始頁: 8395
結束頁: 8400
顯示於類別:期刊論文


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