Application for Web Text Categorization Based on Support Vector Machine
This paper put forward a text categorization method based on Naive Bayes learning support vector machine. First adopt the text pre-processing. Then vector space model and linked list of technical are used to extract text features, reduce dimensions according to the characteristics of the text Then, after Naive Bayes algorithm been proposed to train the support vector machines, support vector machines is used to new text categorization. Then the experiment method and result are given. The results show that the method propsed are not only more reliable, but also further improve the precision classification comparing with traditional support vector machines algorithm.
Naive Bayes support vector machines (SVM) text categorization algorithm precision
Pan Hao Duan Ying Tan Longyuan
School of Computer Science and Technology, Wuhan University of Technology (WUHT), Wuhan 430070, China
国际会议
重庆
英文
524-527
2009-12-25（万方平台首次上网日期，不代表论文的发表时间）