The communication via email is one of the most popular services of the Internet. Emails have brought us great convenience in our daily work and life. However, unsolicited messages or spam, flood our email boxes, which results in bandwidth, time and money wasting. To this end, this paper presents a rough set based model to classify emails into three categories - spam, no-spam and suspicious, rather than two classes (spam and non-spam) in most currently used approaches. By comparing with popular classification methods like Naive Bayes classification, the error ratio that a non-spam is discriminated to spam can be reduced using our proposed model.
History
Pagination
403 - 408
Location
Kagawa, Japan
Open access
Yes
Start date
2005-05-19
End date
2005-05-21
ISBN-13
9780780390355
ISBN-10
0780390350
Language
eng
Notes
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Publication classification
E1 Full written paper - refereed
Copyright notice
2005, IEEE
Editor/Contributor(s)
H Tarumi, Y Li, T Yoshida
Title of proceedings
Proceedings of the 2005 International Conference on Active Media Technology : (AMT2005) : May 19-21, 2005, Kagawa International Conference Hall, Takamatsu, Kagawa, Japan