Telecom customer segmentation with K-means clustering

Author

Ye, Luo ; Qiu-ru, Cai ; Hai-xu, Xi ; Yi-jun, Liu ; Zhi-min, Yu

Author_Institution

Sch. of Comput. Eng., Jiangsu Teachers Univ. of Technol., Changzhou, China

fYear

2012

fDate

14-17 July 2012

Firstpage

648

Lastpage

651

Abstract

Development of data mining application is very important for the telecommunication enterprise, which is a typical data-intensive industry. Customer segmentation can help analyze customer composition accurately and promote the quality of service and marketing. Using K-means clustering and the commercial automatic data mining tool KXEN, the paper proposes a resolution of customer segmentation for Changzhou telecom in Jiangsu province. Results show that the resolution is effective and successful.

Keywords

customer services; data mining; pattern clustering; telecommunication industry; Changzhou telecom; Jiangsu province; KXEN; automatic data mining tool; customer composition analysis; data-intensive industry; k-means clustering; telecom customer segmentation resolution; telecommunication enterprise; Algorithm design and analysis; Clustering algorithms; Data mining; Educational institutions; Market research; Telecommunications; Customer segmentation; K-means clustering; KXEN software; Telecom;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science & Education (ICCSE), 2012 7th International Conference on

Conference_Location

Melbourne, VIC

Print_ISBN

978-1-4673-0241-8

Type

conf

DOI

10.1109/ICCSE.2012.6295158

Filename

6295158