Anti-spam Filters Based on Support Vector Machines

被引：0

作者：

Xie, Chengwang ^{[1
]}

Ding, Lixin ^{[1
]}

Du, Xin ^{[1
]}

机构：

[1] Wuhan Univ, State Key Lab Software Engn, Wuhan 430072, Peoples R China

来源：

ADVANCES IN COMPUTATION AND INTELLIGENCE, PROCEEDINGS | 2009年 / 5821卷

关键词：

anti-spam; support vector machines; classification; filter;

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：

Recently, spam has become an increasingly important problem. In this paper, a support vector machine (SVM) is used as the spam filter. Then a study is made of the effect of classification error rate when different subsets of corpora are used, and of the filter accuracy when SVM's with linear, polynomial, or RBF kernels is used. Also an investigation is made of the effect of the size of attribute sets. Based on the experimental results and analysis, it is concluded that SVM will be a very good alternative for building anti-spam classifiers, with consideration of a good combination of accuracy, consistency, and speed.

引用

页码：349 / 357

页数：9

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