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
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;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location :
Shandong
Print_ISBN :
978-0-7695-3305-6
DOI :
10.1109/FSKD.2008.12
