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
收藏
页码：719 / 722
页数：4
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