垃圾邮件过滤的贝叶斯方法综述

目前，基于内容的垃圾邮件过滤问题是Internet安全技术研究的一个重点问题，将机器学习的相关方法应用于垃圾邮件的搜索和判定是进行大量垃圾邮件处理的有效方法。由于贝叶斯分类方法在垃圾邮件处理上表现出了很高的准确度，因此基于贝叶斯分类的垃圾邮件分类方法受到了广泛的关注。主要介绍了贝叶斯方法的理论依据和实现方法，总结了近几年的贝叶斯分类方法的研究情况和贝叶斯方法在垃圾邮件处理中应用的优点和局限性，并提出了下一步可能的研究方向。

Survey of Application of Bayesian Classifying Method to Spam Filtering

The study on content-based spam filtering is one of the hot topics in the Internet security research area all over the world recently. Since spam filtering is a classification problem, all classifying method in machine-learning could be applied to the field. Among them, Bayesian classify method has expressed high accuracy. In this paper, the basic theory of Bayesian classifying method is described in detail, and different implementation methods are compared and summarized. Also, limitation of Bayesian method is evaluated and the research direction in future is proposed according to the limitation.