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Study on web classification mining method based on fuzzy neural network

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3 Author(s)
Jingwen Tian ; Coll. of Autom., Beijing Union Univ., Beijing, China ; Meijuan Gao ; Yang Sun

With the development and widely used of Internet and information technology, the Web has become one of the most important means to obtain information for people. According to the Web document classification and the theory of artificial neural network, a Web classification mining method based on fuzzy neural network (FNN) is presented in this paper. We construct the structure of fuzzy neural network that used for Web text information classification, and adopt the Levenberg-Marquart optimizing algorithm to train fuzzy neural network, thereby enhancing the convergence rate and the classification accuracy. The structure of Web classification mining system based on fuzzy neural network is given. With the ability of strong self-learning and nonlinear function approach and pattern classification of fuzzy neural network, the classification mining method can truly classify the Web text information. The actual classification results show that this method is feasible and effective.

Published in:

Automation and Logistics, 2009. ICAL '09. IEEE International Conference on

Date of Conference:

5-7 Aug. 2009

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