Mail Filtering Algorithm Based on The Feedback Correction Probability Learning

Abstract

With the popularity of the Internet, e-mail with its fast and convenient advantages has gradually developed into one of the important communication tools in people's lives.However, the problem of followed spam is increasingly severe, it is not only the dissemination of harmful information, but also waste of public resources.To solve this problem, the author proposed a mail filtering algorithm based on the feedback correction probability learning.The feedback correction probability training has less feedback learning data and use error-driven training in order to achieve a high classification effect.The experiment also tested the idea.