Using LPP and LS-SVM for spam filtering

Author

Sun, Xia ; Zhang, Qingzhou ; Wang, Ziqiang

Author_Institution

Sch. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou, China

Volume

2

fYear

2009

fDate

8-9 Aug. 2009

Firstpage

451

Lastpage

454

Abstract

To efficiently deal with spam mail filtering problem, a novel spam filtering algorithm based on locality pursuit projection (LPP) and least square version of SVM(LS-SVM) is proposed in this paper. The mail message features are first extracted by the LPP algorithm, then the LS-SVM classifier is used to classify mails into spam and legitimate. Experimental results demonstrate that the proposed algorithm performs much better than other related spam filtering algorithms.

Keywords

Internet; classification; e-mail filters; feature extraction; least squares approximations; pattern classification; support vector machines; text analysis; unsolicited e-mail; Internet; LPP algorithm; LS-SVM classifier; least square version-of-SVM classifier; locality pursuit projection algorithm; mail message feature extraction; spam mail filtering algorithm; text classification; Feature extraction; Filtering algorithms; Information filtering; Information filters; Large scale integration; Postal services; Principal component analysis; Support vector machine classification; Support vector machines; Text categorization; LS-SVM; locality pursuit projection (LPP); spam filtering; text classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on

Conference_Location

Sanya

Print_ISBN

978-1-4244-4247-8

Type

conf

DOI

10.1109/CCCM.2009.5267466

Filename

5267466