Classify Text-based Email Using Naive Bayes Method With Small Sample

With the popularity of the Internet, e-mail has gradually become one of the important communication tools for people's work and life with its fast and convenient advantages. However, the problem of spam has become increasingly serious. It not only spreads harmful information, but also consumes a lot of public resources and infringes the legitimate rights and interests of e-mail users and enterprises. Although there are many spam filtering methods at present, the situation that spam does not fall but rises shows that the existing spam filtering methods have not achieved ideal filtering effect. This paper uses naive Bayesian method and small sample to classify e-mail, and combines Chinese information processing technology to propose an efficient filtering system BETSY. The experimental results show that the method proposed in this paper has achieved good results and has direct application value.