Performance Analysis of Chinese Webpage Categorizing Algorithm Based on Support Vector Machines (SVM)

摘要：

Categorizing web automatically for users is a key technique of information society, and the key point of this technique is web training and categorization. This paper researches one of the important algorithm in this field—support vector machines (SVM). By analyzing and simulating 4 kinds of kernel function and 3 ways of feature selection, polynomial kernel function and document frequency is chosen for the best way in SVM algorithm. Meanwhile, pre-process algorithm is given in this paper in order to improve the efficiency of categorization. By simulation, importing pre-process method to SVM enhances the capability of the web categorization both in precision and time-consumption.

作者: Xiao Gang Xie Jiancang

作者单位: School of Business Administration,Xian University of Technology,Xian 710048,China;Xidian Universit School of Business Administration,Xian University of Technology,Xian 710048,China

会议类型: 国际会议

会议名称: The Fifth International Conference on Information Assurance and Security(第五届信息保障与安全国际会议)

会议地点: 西安

会议语种:英文

页码: 231-235

在线出版日期: 2009-08-18（万方平台首次上网日期，不代表论文的发表时间）