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Spamcooling : a parallel heterogeneous ensemble spam filtering system based on active learning techniques

Wang, Jinlong, Gao, Ke and Vu, Huy Quan 2010, Spamcooling : a parallel heterogeneous ensemble spam filtering system based on active learning techniques, Journal of convergence information technology, vol. 5, no. 4, pp. 90-102.

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Title Spamcooling : a parallel heterogeneous ensemble spam filtering system based on active learning techniques
Author(s) Wang, Jinlong
Gao, Ke
Vu, Huy Quan
Journal name Journal of convergence information technology
Volume number 5
Issue number 4
Start page 90
End page 102
Total pages 13
Publisher Advanced Institute of Convergence IT
Place of publication Korea
Publication date 2010-06
ISSN 1975-9320
2233-9299
Keyword(s) ensemble learning
active learning
spam filtering
Summary Anti-spam technology is developing rapidly in recent years. With the emerging applications of machine learning in diverse fields, researchers as well as manufacturers around the world have attempted a large number of related algorithms to prevent spam. In this paper, we designed an effective anti-spam protection system, SpamCooling, based on the mechanism of active learning and parallel heterogeneous ensemble learning techniques. The system adopts a batch method to filter spam and can be easily incorporated with existing mail clients (MUA). It can actively obtain user feedbacks for providing users with personalized spam filtering experiences. The parallel heterogeneous ensemble method can help system achieve high spam detection rate as well as low ham misclassification rate.
Language eng
Field of Research 080303 Computer System Security
Socio Economic Objective 890206 Internet Hosting Services (incl. Application Hosting Services)
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2010
Persistent URL http://hdl.handle.net/10536/DRO/DU:30034431

Document type: Journal Article
Collection: School of Information Technology
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