A statistical approach to the spam problem
Linux Journal
An evaluation of statistical spam filtering techniques
ACM Transactions on Asian Language Information Processing (TALIP)
Evaluation of spam detection and prevention frameworks for email and image spam: a state of art
Proceedings of the 10th International Conference on Information Integration and Web-based Applications & Services
Behavior-based spam detection using a hybrid method of rule-based techniques and neural networks
Expert Systems with Applications: An International Journal
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Recently, a statistical filtering based on Bayes theory, so-called Bayesian filtering gain attention when it was described in the paper “A Plan for Spam” by Paul Graham, and has become a popular mechanism to distinguish spam email from legitimate email. Many modern mail programs make use of Bayesian spam filtering techniques. The implementation of the Bayesian filtering corresponding to the email written in English and Japanese has already been developed. On the other hand, few work is conducted on the implementation of the Bayesian spam corresponding to Chinese email. In this paper, firstly, we adopted a statistical filtering called as bsfilter and modified it to filter out Chinese email. When we targeted Chinese emails for experiment, we analyzed the relation between the parameter and the spam judgement accuracy of the filtering, and also considered the optimal parameter values.