Abstract: In this paper, we studied the algorithm of E-mail classification using nave Bayes classification. The concepts of Fizz Network and Fizz Degree were proposed. We presented the algorithm to depict the communication network of criminous orgnization, and the algorithm for structure mining. Finally, the experiments prove the good performance of the proposed algorithm.

Key words: E-mail, bayesian algorithm, naive bayes classification, fizz network, fizz degree

摘要： 研究了利用朴素贝叶斯分类算法对电子邮件进行分类处理，引入了活跃网络和活跃度的概念，提出了犯罪组织通讯网络的描述算法以及组织结构的挖掘算法，实验证明了算法的有效性。

关键词: 电子邮件, 贝叶斯算法, 朴素贝叶斯分类算法, 活跃网络, 活跃度