Research on E-mail Filtering Based On Improved Bayesian

Abstract

Naive Bayesian has been widely used in spam filter because it simply and it also could classify texts more correctly and quickly. However, in the process of classifying and filtering, the traditional method doesn't consider the different features between the spam mail and the legitimate mail, and it also doesn't take into account the loss of misclassifying legitimate mail as spam, so there are many limitations of e-mail filtering. An improved algorithm based on Naïve Bayesian and Boosting method is proposed in this paper. The experiment result shows that the improved algorithm has better performance.