Title :
An Efficient SVM-Based Spam Filtering Algorithm
Author :
Wang, Zi-qiang ; Sun, Xia ; Li, Xin ; Zhang, De-Xian
Author_Institution :
Sch. of Inf. Sci. & Eng., Henan Univ. of Technol., Zhengzhou
Abstract :
The electronic mail (e-mail) concept makes it possible to communicate with many people in an easy and cheap way. Though email brought us such huge convenience, it also caused us trouble of managing the large quantities of spam mails received everyday. Without appropriate counter-measures, the situation seems to be worsening and spare email will eventually undermine the usability of email. To efficiently solve the above problems, a spam mail filtering method using feature selection and support vector machine is proposed in this paper. The experimental results show that the proposed method outperforms other conventional spam filtering method
Keywords :
classification; feature extraction; information filtering; support vector machines; text analysis; unsolicited e-mail; SVM-based spam mail filtering algorithm; electronic mail; feature selection; support vector machine; text categorization; Bayesian methods; Electronic mail; Filtering algorithms; Information filtering; Information filters; Machine learning; Postal services; Support vector machine classification; Support vector machines; Text categorization; Unsolicited electronic mail; Feature selection; SVM; Spam filtering; Text classification;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258626