DocumentCode :
424122
Title :
Clustering anaslysis of customer relationship in securities trade [anaslysis read analysis]
Author :
Wang, Zhong ; Pi-Lian He ; Guo, Lan-Shen ; Zheng, Xiao-Shen
Author_Institution :
Sch. of Electron. & Inf., Tianjin Univ., China
Volume :
3
fYear :
2004
fDate :
26-29 Aug. 2004
Firstpage :
1760
Abstract :
This paper applies data mining technology to customer relationship management of securities industry and presents securities business model of CRM based on customer clustering methods. In class classification layer, hierarchical clustering model is used to realize customer classification according to such indexes as trading frequency, trading capacity and interest balance. In the group classification layer, according to customers´ operating style, dynamic Bayes model is adopted in order to group customers. The securities business model and its customer clustering methods have been applied in CITIC Securities Co. Ltd and have achieved successful effect on customer service.
Keywords :
Bayes methods; customer relationship management; data mining; pattern classification; pattern clustering; securities trading; class classification layer; clustering analysis; customer classification; customer clustering methods; customer relationship management; customer service; data mining technology; dynamic Bayes model; group classification layer; hierarchical clustering model; securities business model; securities industry; securities trade; Clustering methods; Companies; Customer relationship management; Data mining; Data security; Data warehouses; Marketing management; National security; Resource management; Technology management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
Type :
conf
DOI :
10.1109/ICMLC.2004.1382060
Filename :
1382060
Link To Document :
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