Evolutionary support vector machines for spam filtering

被引：0

作者：

Stoean, Ruxandra ^{[1
]}

Stoean, Catalin ^{[1
]}

Preuss, Mike ^{[1
]}

Dumitrescu, D. ^{[1
]}

机构：

[1] Univ Craiova, Fac Math & Comp Sci, Dept Comp Sci, Craiova, Romania

来源：

5TH ROEDUNET IEEE INTERNATIONAL CONFERENCE, PROCEEDINGS | 2006年

关键词：

classification; evolutionary algorithms; evolutionary support vector machines; spam filtering;

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：

As the number and threat of unsolicited commercial e-mails seems to be increasing day by day, the need for powerful techniques that are able to combat the intrusion of these e-mails is immense. In this respect, present paper proposes a recently developed technique born through hybridization between the successful learning paradigm of support vector machines and the strong optimization potential of evolutionary algorithms. Suggested learning technique is applied to a large set of data containing information about 4601 e-mails; for each e-mail there are records about frequencies of words and other relevant data adding up to a total of 57 attributes. Obtained results encourage further investigation.

引用

页码：261 / 265

页数：5

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