DocumentCode
1946518
Title
An email classification model based on rough set theory
Author
Zhao, Wenqing ; Zhang, Zili
Author_Institution
Sch. of Comput. Sci. & Technol., North China Electr. Power Univ., Baoding, China
fYear
2005
fDate
19-21 May 2005
Firstpage
403
Lastpage
408
Abstract
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.
Keywords
Bayes methods; Internet; authorisation; pattern classification; rough set theory; unsolicited e-mail; Internet; Naive Bayes classification; email box; email classification model; rough set theory; spam classification; unsolicited messages; Classification tree analysis; Decision trees; Electronic mail; Error analysis; Filtering; Internet; Set theory; Support vector machine classification; Support vector machines; Unsolicited electronic mail;
fLanguage
English
Publisher
ieee
Conference_Titel
Active Media Technology, 2005. (AMT 2005). Proceedings of the 2005 International Conference on
Print_ISBN
0-7803-9035-0
Type
conf
DOI
10.1109/AMT.2005.1505383
Filename
1505383
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