Abstract: Naive Bayesian classification algorithm is an effective spam filtering method. Information on the Internet changed over time and generated new concepts. The recent spam tokens were an important basis for spam filtering. In this approach,new spam tokens were recorded separately according to their time series and those tokens got higher prior probability in the email classification. Experimental results show that the proposed algorithm has higher accuracy,precision and recall than the traditional Nave Bayesian spam filtering method.