An optimal svm-based text classification algorithm

被引：0

作者：

Wang, Zi-Qiang ^{[1
]}

Sun, Xia ^{[1
]}

Zhang, De-Xian ^{[1
]}

Li, Xin ^{[1
]}

机构：

[1] Henan Univ Technol, Sch Informat & Engn, Zhengzhou 450052, Peoples R China

来源：

PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2006年

基金：

中国国家自然科学基金;

关键词：

text classification; SVM; optimal strategies;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The goal of a text classification system is to determine whether a given document belongs to which of the predefined categories. An optimal SVM algorithm for text classification via multiple optimal strategies is proposed in this paper. The experimental results indicate that the proposed optimal classification algorithm yields much better performance than other conventional algorithms.

引用

页码：1378 / +

页数：2

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