New text classification method based on HMM-SVM

被引：0

作者：

Wang, Jing ^{[1
]}

Yao, Yong ^{[1
]}

Liu, ZhiJing ^{[1
]}

机构：

[1] Xidian Univ, Sch Comp Sci & Technol, Xian 710071, Peoples R China

来源：

2007 INTERNATIONAL SYMPOSIUM ON COMMUNICATIONS AND INFORMATION TECHNOLOGIES, VOLS 1-3 | 2007年

关键词：

text classification; feature extraction; hidden Markov model; support vector machine;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Text classification has been considered as a hot research area in data mining. This paper presents a new approach combining Hidden Markov Model (HMM) with Support Vector Machine (SVM) for text classification. HMMs are used to as a feature extractor and then a new feature vector is normalized as the input of SVMs, so the trained SVMS can classify unknown texts successfully. The experimental results demonstrate that the new method has a very high precision.

引用

页码：1516 / 1519

页数：4

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