Document Classification Algorithm Based on IB and LS-SVM

被引：0

作者：

Wang, Ziqiang ^{[1
]}

Sun, Xia ^{[1
]}

机构：

[1] Henan Univ Technol, Sch Informat Sci & Engn, Zhengzhou 450000, Peoples R China

来源：

2009 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL 1, PROCEEDINGS | 2009年

关键词：

document classification; feature selection; information bottleneck (IB); least square SVM(LS-SVM); TEXT CATEGORIZATION;

D O I：

10.1109/IITA.2009.65

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Document classification has received extensive attention in the past few decades due to its wide applications in many fields. To efficiently deal with this problem, a novel document classification algorithm based on information bottleneck (IB) and least square version of SVM(LS-SVM) is proposed in this paper. Extensive experimental results on the real-word document corpus show that the proposed algorithm achieves much better performance than SVM algorithm.

引用

页码：279 / 282

页数：4

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