Applying Modified Fuzzy Neural Network to Customer Classification of E-Business

  • Yukun Cao
  • Yunfeng Li
  • Xiaofeng Liao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3828)


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.


Radial Basis Function Neural Network User Interest Customer Behavior Adaptive Resonance Theory Vigilance Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yukun Cao
    • 1
  • Yunfeng Li
    • 1
  • Xiaofeng Liao
    • 1
  1. 1.Department of Computer ScienceChongqing UniversityChongqingP.R.China

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