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
Link To Document :
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