A user classification for internet content provider based modified fuzzy neural network

Authors:
Yunfeng Li;Yukun Cao
Affiliations:
Department of Computer Science, Chongqing University, Chongqing, P.R. China;Department of Computer Science, Chongqing University, Chongqing, P.R. China
Venue:
ICADL'05 Proceedings of the 8th international conference on Asian Digital Libraries: implementing strategies and sharing experiences
Year:
2005

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Abstract

With the explosive growth of the Internet, it has entered the age led by ICP (internet content provider). Helping users to locate relevant information in an efficient manner is very important both do the person and to the ICPs. As such, it is highly desired to have a systematic system for extracting user features effectively, and subsequently, analyzing user orientations quantitatively. The experimental results of this clustering technique show the promise of our system. 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 user clustering method should be performed prior to ICPs as the basis to provide personalized service. The experimental results of this clustering technique show the promise of our system. The scheme could be used in local data management application, digital library, and so on.