DocumentCode
477788
Title
Online Linear Discriminative Learning for Spam Filter
Author
Qi, Haoliang ; He, Xiaoning ; Yang, Muyun ; Li, Jun ; Lei, Guohua ; Han, Zhongyuan ; Li, Sheng
Author_Institution
Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin
Volume
2
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
306
Lastpage
309
Abstract
This paper describes a simple but effective discriminative learner for spam filter. We statically derive the features within Bayesian framework, cluster them into groups according to their position and then assigning weights respectively. The model is evaluated by TREC Spam corpus and compared with the TREC results. Experimental results show that our linear discriminative model can produce competitive results.
Keywords
Bayes methods; e-mail filters; information filters; learning (artificial intelligence); unsolicited e-mail; Bayesian framework; TREC Spam corpus; online linear discriminative learning; spam filter; Bayesian methods; Computer science; Feature extraction; Filtering; Fuzzy systems; Machine learning; Nonlinear filters; Text categorization; Unsolicited electronic mail; Vectors; Bayes rule; Spam filtering; n-grams; online discriminative learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location
Shandong
Print_ISBN
978-0-7695-3305-6
Type
conf
DOI
10.1109/FSKD.2008.12
Filename
4666128
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