DocumentCode :
3167209
Title :
Customer segmentation for B2C e-commerce websites based on the Generalized association rules and decision tree
Author :
Ma, Haiying ; Gang, Dong
Author_Institution :
Dept. of Manage. Sci. & Eng., East China Univ. of Sci. & Technol., Shanghai, China
fYear :
2011
fDate :
8-10 Aug. 2011
Firstpage :
4600
Lastpage :
4603
Abstract :
Today, as the rapid popularization of Internet applications, many Chinese businesses are attracted by huge profits and market space of e-commerce, beginning to join the area of e-commerce. How to keep effective customer, attract more members of the e-commerce website and expand the market effectively, is the problem that all the managers most concerned about. Through studying and comparing common customer segmentation models, this article is proposing a integrated model that combines the techniques of generalized association rules and decision tree. This model is used for customer segmentation for e-commerce websites. It can help managers understand customers, develop markets, and support decision-making.
Keywords :
Internet; Web sites; customer profiles; data mining; decision trees; electronic commerce; profitability; B2C e-commerce Web sites; Chinese businesses; Internet application; customer relationship management; customer segmentation model; decision making support; decision tree; e-commerce market space; generalized association rules; profitability; Association rules; Banking; Business; Credit cards; Decision trees; Internet; Association Rules; Customer Segmentation; Decision Tree; E-commerce Introduction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location :
Deng Leng
Print_ISBN :
978-1-4577-0535-9
Type :
conf
DOI :
10.1109/AIMSEC.2011.6010255
Filename :
6010255
Link To Document :
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