Feature selection and text classification for Chinese web documents

被引：0

作者：

Xu, JC ^{[1
]}

Liu, DY ^{[1
]}

Hu, M ^{[1
]}

机构：

[1] Changchun Univ Technol, Sch Comp Sci & Engn, Seoul 130012, South Korea

来源：

PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2004年

关键词：

feature selection; data-mining; information retrieval; web-mining;

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：

A great deal of methods for feature selection and text classification have been widely applied to English web documents, while few studies have been done on Chinese web documents. This paper gives a term weighting method based on inverse document frequency, html tags and length of Chinese phrase, reports our method to select web text feature based on the messy genetic algorithm, provides an algorithm tor web text classification based on improvement on lattice machine approach. Our experiments show that these methods are valuable.

引用

页码：1304 / 1309

页数：6

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