一种混合的垃圾邮件过滤算法研究

Research of a Hybrid Spam Filtering Algorithm

贝叶斯邮件过滤器具有较强的分类能力,极高的准确率,在内容过滤领域占据主导地位。人工免疫系统具备强大的自学习、自适应,鲁棒性等能力,已发展成为计算智能研究的一个崭新的分支。该文在分析贝叶斯的原理和人工免疫的仿生机理的基础上,将贝叶斯与人工免疫相结合,设计和实现了一种基于贝叶斯和人工免疫的混合垃圾邮件过滤算法,并利用现有的垃圾邮件语料库得到预期的实验结果。

Bayes filtering has a dominant place in the area of spare filtering for its strong categorization and high precision. Artificial immune system has become a new embranchment in computing intelligence for its good self-learning, self-adaptability, and robusticity. This paper analyzes the basic principle of Bayes and artificial immune systems, proposes a hybrid spare filtering algorithm based on Bayes and artificial immune system, and then designs and develops the spam filtering system based on this algorithm. It is proved that this system is effective to filter spare in English and Chinese e-mail corpus.