Statistical-Based Bayesian Algorithm for Effective Email Classification

Email is an incontestable communication mode in both professional and personal correspondences. The survey shows that an ordinary white-collar worker spend at least an hour every day to deal with the email. Handling spam which is disguised as normal email is waste our time. In this paper, we propose a spam detection method upon statistical-based Bayesian algorithm. Firstly, the method use actual priori probability of spam instead of constant probability. Secondly, the selective range and rules of tokens is improved. Finally, our method add URLs and images into detection content. The experiment result shows that the improved statistical-based Bayesian classification algorithm works well in practice.