Design of Text Categorization System Based on SVM

摘要：

　　This paper introduces the design of a text categorization system based on Support Vector Machine (SVM).It analyzes the high dimensional characteristic of text data,the reason why SVM is suitable for text categorization.According to system data flow this system is constructed.This system consists of three subsystems which are text representation,classifier training and text classification.The core of this system is the classifier training,but text representation directly influences the currency of classifier and the performance of the system.Text feature vector space can be built by different kinds of feature selection and feature extraction methods.No research can indicate which one is the best method,so many feature selection and feature extraction methods are all developed in this system.For a specific classification task every feature selection method and every feature extraction method will be tested,and then a set of the best methods will be adopted.

关键词： SVM VSM text categorization feature selection feature extraction

作者: Zhenyan Liu Weiping Wang Yong Wang

作者单位: Institute of Computing Technology,Chinese Academy of Sciences, China;Graduate University, Chinese Ac Institute of Computing Technology,Chinese Academy of Sciences, China School of Software, Beijing Institute of Technology, China

会议类型: 国际会议

会议名称: 2012 2nd international Conference on Materials Science and Information Technology(2012第二届材料科学与信息技术国际会议)(MSIT2012)

会议地点: 西安

会议语种:英文

页码: 1191-1195

在线出版日期: 2012-08-24（万方平台首次上网日期，不代表论文的发表时间）