邻近类别分类在电子邮件过滤系统中的运用

电子邮件作为互联网技术发展的产物，在给全球网民带来通讯便利的同时，正不可避免地遭遇有悖初衷的运用。最为突出的是随之产生的垃圾邮件像瘟疫一样蔓延，污染网络环境，占用大量传输、存储和运算资源，影响了网络的正常运行。垃圾邮件问题日益严重，受到研究人员的广泛关注。基于内容的过滤是当前解决垃圾邮件问题的主流技术之一。由于常用的特征字串匹配技术对垃圾邮件件的查准率已经不能满足日益提高的过滤系统用户的产品需求，随后引入邻近类别分类的方法，利用基于贝叶斯算法的电子邮件过滤系统，对色情垃圾邮件样本进行分析，可明显提高对垃圾邮件的查准率。

Vicinity CategOry Classification in Email Filtering System

As the product of Internet technology,Email can provide convenient communication.On the other hand,some applications related to Email cause big trouble to the Internet.For example,the spam spreads like plague,polluting the net environment,occupying resources for transmission,storation and calculation, and influencing the normal operation of network.The volume of junk Email in Internet has grown tremendously in the past few years.And this problem attracts many researchers' attention.Because the finding spam on feature word matching technique can not satisfy the developing requirements of filtering system user.Referred the vicinity category classification to the Email filtering system that based on the Bayesian can filter pornographic counteraction and spam related to advertisement.Till this time,has some test results which showed the high call ration to pornographic spam.