An improved text feature selection method based on key words

摘要：

Vector space model is commonly used in the formal representation on text, but this approach would not highlight the features which play a key role in the text contents. An improved feature selection method based on key words was proposed, which uses text structural information and mutual information theory to extract key words on text content. Through using support vector machine (SVM) classifier to test, results showed that classification accuracy has improved significantly.

关键词： text classification text feature selection vector space model support vector machine

作者: ZHANG Hong-wei CAO Jian-fang FENG Su-qin

作者单位: Department of Electronics Xinzhou Teachers University Xinzhou, China Department of Computer Science Xinzhou Teachers University Xinzhou, China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 293-297

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）