An improved text feature selection method based on key words

Zhang Hong-wei,Cao Jian-fang,Su-qin Feng

Proceedings - 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010（2010）

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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. ©2010 IEEE.

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关键词

support vector machine,text classification,text feature selection,vector space model,information theory,text analysis,support vector machines,mutual information,feature extraction,feature selection,manganese

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