The Research on SVM Multi-classification and Its Application in Chinese Question Classification
Support Vector Machine (SVM) is originally used for binary classification. How to popularize the result of two-class classification to multi-class classification has been a problem which needs to be more discussed and investigated. A general overview of existing representative methods for multi-category support vector machines is presented and their performances are compared in the paper. Then, the algorithms are applied in the Chinese question classification. The paper also discusses Chinese question classification hierarchy and the feature selection of the question. Then, we apply the four SVM multi-classification algorithms to Chinese question classification and do some contrast experiments. The result of the experiments shows that the binary-tree algorithm is more effective than the other algorithms in the Chinese question classification.
Support Vector Machine Multi-category classification Chinese question classification
Zhang Wei Duan Liguo Chen Junjie Zhang Wei
Computer and Software College Taiyuan University of Technology Taiyuan, China Information Center Shanxi Medical College for Continuing Education Taiyuan, China
国际会议
2010 International Conference on Software and Computing Technology(2010年软件与计算机技术国际会议 ICSCT 2010)
昆明
英文
232-235
2010-10-17（万方平台首次上网日期，不代表论文的发表时间）