文献类型：会议论文

英文题名：Web Classification Mining Based on Radial Basic Probabilistic Neural Network

作者：Gao, Meijuan[1];Tian, Jingwen[1]

第一作者：高美娟

通讯作者：Gao, MJ[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 International Workshop on Database Technology and Applications

会议日期：APR 25-26, 2009

会议地点：Wuhan, PEOPLES R CHINA

语种：英文

外文关键词：Web mining; classification; radial basic function; probabilistic 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 radial basic probabilistic neural network is presented in this paper. We construct the structure of radial basic probabilistic neural network that used for web text information classification, and adopt the K-Nearest Neighbor algorithm and least square method to train the network. The structure of web classification mining system based on radial basic probabilistic neural network is given. With the ability of strong pattern classification and function approach and fast convergence of radial basic probabilistic 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.