文献类型：会议论文

英文题名：Research of Web Classification Mining Based on Wavelet Neural Network

作者：Tian, Jingwen[1];Gao, Meijuan[1]

通讯作者：Tian, JW[1]

机构：[1]Beijing Union Univ, Dept Automat Control, 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, Dept Automat Control, 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：1st IITA International Joint Conference on Artificial Intelligence

会议日期：APR 25-MAY 26, 2009

会议地点：Hainan Isl, PEOPLES R CHINA

语种：英文

外文关键词：Web mining; classification; wavelet neural network

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 wavelet neural network is presented in this paper. Moreover, we adopt a algorithm of reduce the number of the wavelet basic function by analysis the sparseness property of sample data which can optimize the wavelet network in a large extent, and the learning algorithm based on the gradient descent was used to train network. The structure of web classification mining system based on wavelet neural network is given. With the ability of strong nonlinear function approach and pattern classification and fast convergence of wavelet 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.