Web Classification Mining Based on Radial Basic 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.