A WordNet-based approach to feature selection in text categorization

被引：1

作者：

Zhang, K ^{[1
]}

Sun, J ^{[1
]}

Wang, B ^{[1
]}

机构：

[1] Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China

来源：

INTELLIGENT INFORMATION PROCESSING II | 2005年 / 163卷

关键词：

feature selection; WordNet; text categorization;

D O I：

10.1007/0-387-23152-8_59

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a new feature selection method for text categorization. In this method, word tendency, which takes related words into consideration, is used to select best terms. Our experiments on binary classification tasks show that our method achieves better than DF and IG when the classes are semantically discriminative. Furthermore, our best performance is usually achieved in fewer features.

引用

页码：475 / 484

页数：10