Research of web classification mining based on classify support vector machine

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 classify support vector machine (SVM) is presented in this paper. The SVM network structure that used for Web text information classification is established, and we use the genetic algorithm (GA) to optimize SVM parameters, thereby enhancing the convergence rate and the classification accuracy. The structure of Web classification mining system based on classify support vector machine is given. With the ability of strong pattern classification and self-learning and well generalization of SVM, the classification mining method can truly classify the web text information. The actual classification results show that this method is feasible and effective.