Enhancement of DTP feature selection method for text categorization

被引：0

作者：

Moyotl-Hernández, E ^{[1
]}

Jiménez-Salazar, H ^{[1
]}

机构：

[1] Univ Autonoma Puebla, Fac Ciencias Comp, Puebla 72570, Mexico

来源：

COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING | 2005年 / 3406卷

关键词：

D O I：

暂无

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 studies the structure of vectors obtained by using term selection methods in high-dimensional text collection. We found that the distance to transition point (DTP) method omits commonly occurring terms, which are poor discriminators between documents, but which convey important information about a collection. Experimental results obtained on the Reuters-21578 collection with the k-NN classifier show that feature selection by DTP combined with common terms outperforms slightly simple document frequency.

引用

页码：719 / 722

页数：4

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