Robust segmentation for the service industry using kernel induced fuzzy clustering techniques

Chih-Hsuan Wang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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 dissatisfactory 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 supervised WINE and the unsupervised 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 simultaneously.

Original languageEnglish
Title of host publicationIEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management
Pages2197-2201
Number of pages5
DOIs
StatePublished - 1 Dec 2009
EventIEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2009 - Hong Kong, China
Duration: 8 Dec 200911 Dec 2009

Publication series

NameIEEM 2009 - IEEE International Conference on Industrial Engineering and Engineering Management

Conference

ConferenceIEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2009
CountryChina
CityHong Kong
Period8/12/0911/12/09

Keywords

  • Customer relationship management
  • Kernel induced fuzzy clustering
  • Robust classification
  • Robust segmentation

Fingerprint Dive into the research topics of 'Robust segmentation for the service industry using kernel induced fuzzy clustering techniques'. Together they form a unique fingerprint.

Cite this