A survey on dimension reduction techniques in text classification

被引：0
|
作者：
Wang, Zhi Juan [1 ,2 ]
Zhou, Ruo Song [1 ]
机构：
[1] Minzu Univ China, Coll Informat Engn, Beijing, Peoples R China
[2] Natl Language Resource Monitoring & Res Ctr, Minor Languages Branch, Beijing, Peoples R China
来源：
COMPUTING, CONTROL, INFORMATION AND EDUCATION ENGINEERING | 2015年
关键词：
Dimension reduction; Text classification; Feature selection; Feature extraction; CDF;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Dimension reduction is one of the key points for text classification. Feature selection and feature extraction are the two common methods of dimension reduction. In this paper, we mainly discussed some dimension reduction techniques from two aspects including traditional methods (Information Gain, Mutual Information, Document Frequency, Correlation Coefficient) and new methods (Optimization Mutual Information Based on Word Frequency, CDF (Concentration, Dispersion and Frequency), Semantic Relatedness). Then analyzed the principle of these methods and illustrated their advantages as well as disadvantages.
引用
收藏
页码：633 / 635
页数：3
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