Applying modified fuzzy neural network to customer classification of e-business

Authors:
Yukun Cao;Yunfeng Li;Xiaofeng Liao
Affiliations:
Department of Computer Science, Chongqing University, Chongqing, P.R.China;Department of Computer Science, Chongqing University, Chongqing, P.R.China;Department of Computer Science, Chongqing University, Chongqing, P.R.China
Venue:
WINE'05 Proceedings of the First international conference on Internet and Network Economics
Year:
2005

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Abstract

With the increasing interest and emphasis on customer demands in e-commerce, customer classification is in a crucial position for the development of e-commerce in response to the growing complexity in Internet commerce logistical markets. As such, it is highly desired to have a systematic system for extracting customer features effectively, and subsequently, analyzing customer orientations quantitatively. This paper presents a new approach that employs a modified fuzzy neural network based on adaptive resonance theory to group users dynamically based on their Web access patterns. Such a customer clustering method should be performed prior to Internet bookstores as the basis to provide personalized service. The experimental results of this clustering technique show the promise of our system.