Name
Title | ||
|---|---|---|
The Comparison of Chinese Spam Filter Based on Generative Model and Discriminative Model |
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IALP.2011.64 | IALP |
Keywords | Field | DocType |
bogo system,logistic regression,belief networks,chinese spam filter,typical discriminative model,bogo,english dataset,public chinese datasets,regression analysis,rosvm,bayesian algorithm,relaxed online svm,unsolicited e-mail,public chinese dataset,generative model,spam filter,test dataset,information filters,natural language processing,classical generative model,discriminative model,support vector machines,chinese dataset,lr | Bayesian algorithm,Pattern recognition,Computer science,Regression analysis,Support vector machine,Filter (signal processing),Artificial intelligence,Logistic regression,Discriminative model,Machine learning,Generative model | Conference |
ISBN | Citations | PageRank |
978-1-4577-1733-8 | 1 | 0.38 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong Han | 1 | 1 | 3.42 |
| Yingying Wang | 2 | 21 | 11.64 |
| Huafu Ding | 3 | 1 | 0.38 |
| Haoliang Qi | 4 | 130 | 26.56 |