Spam Filtering System Based on Uncertain Learning

Author

Liu Zhen ; Fu Yan ; Xie Feng-zhu

Author_Institution

Coll. of Comput. Sci. & Eng., UESTC, Chengdu, China

Volume

2

fYear

2009

fDate

7-8 Nov. 2009

Firstpage

141

Lastpage

144

Abstract

Anti-spam system is asked urgently in recent years. Compared with traditional anti-spam system, a new spam filtering system is proposed in this paper which is based on uncertain learning approaches. These uncertain learning approaches are well integrated through a commission collaboration mechanism. The new system could handle dual-way spam filtering, namely both out-going and in-coming spam filtering. Six-month performance test on a real email server proved that the new system has very low FN and FP ratio.

Keywords

information filtering; learning (artificial intelligence); security of data; unsolicited e-mail; antispam system; commission collaboration mechanism; dual-way spam filtering system; email server; uncertain learning approach; Artificial intelligence; Bayesian methods; Collaboration; Computer science; Educational institutions; Filtering algorithms; Iterative algorithms; Kernel; Uncertainty; Unsolicited electronic mail; Commission collaboration mechanism; Dual-way filtering; Spam; Spam weeder;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-3835-8

Electronic_ISBN

978-0-7695-3816-7

Type

conf

DOI

10.1109/AICI.2009.186

Filename

5376416