文献类型：会议论文

英文题名：Study on Web Classification Mining Method Based on Fuzzy Neural Network

作者：Tian, Jingwen[1];Gao, Meijuan[1];Sun, Yang[1]

通讯作者：Tian, JW[1]

机构：[1]Beijing Union Univ, Coll Automat, Beijing, Peoples R China

第一机构：北京联合大学城市轨道交通与物流学院

通讯机构：[1]corresponding author), Beijing Union Univ, Coll Automat, Beijing, Peoples R China.|[1141751]北京联合大学城市轨道交通与物流学院;[11417]北京联合大学;

会议论文集：IEEE International Conference on Automation and Logistics

会议日期：AUG 05-07, 2009

会议地点：Shenyang, PEOPLES R CHINA

语种：英文

外文关键词：Web mining; classification; fuzzy neural network; Levenberg-Marquart algorithm

摘要：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.