DocumentCode
2910216
Title
The Comparison of Chinese Spam Filter Based on Generative Model and Discriminative Model
Author
Han, Yong ; Wang, Yingying ; Ding, Huafu ; Qi, Haoliang
Author_Institution
Comput. Sci. & Technol. Dept., Heilongjiang Inst. of Technol., Harbin, China
fYear
2011
fDate
15-17 Nov. 2011
Firstpage
107
Lastpage
110
Abstract
Previous studies have shown that discriminative model is better than generative model for spam filtering, which is tested on the English dataset. But the study on Chinese Spam Filter is rare. So we compared the performance of Bogo: a classical generative model, Logistic Regression (LR) and Relaxed Online SVM (ROSVM): two typical discriminative models on the Chinese dataset. Bogo system adopts a generative model, which is based on Bayesian algorithm. We choose the public Chinese datasets: TREC06c, SEWM 2008, SEWM 2010, SEWM 2011, as the test dataset with immediate feedback. The discriminative model gives the better results than the generative model based on spam filter. ROSVM gives the best performance on Chinese spam filter.
Keywords
belief networks; information filters; natural language processing; regression analysis; support vector machines; unsolicited e-mail; Bayesian algorithm; Bogo system; Chinese spam filter; English dataset; ROSVM; classical generative model; discriminative model; logistic regression; public Chinese dataset; relaxed online SVM; Filtering; Logistics; Machine learning; Support vector machines; Training; Unsolicited electronic mail; Bogo; Chinese spam filter; LR; ROSVM; discriminative model; generative model;
fLanguage
English
Publisher
ieee
Conference_Titel
Asian Language Processing (IALP), 2011 International Conference on
Conference_Location
Penang
Print_ISBN
978-1-4577-1733-8
Type
conf
DOI
10.1109/IALP.2011.64
Filename
6121481
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