基于朴素贝叶斯和支持向量机的自适应垃圾短信过滤系统

随着短信业务的不断发展，垃圾短信的特征和内容也在不断变化，传统垃圾短信过滤系统中存在的主要问题是，短信特征和内容未能得到及时更新而导致过滤性能降低。考虑朴素贝叶斯的快速统计分类及支持向量机（SVM）的增量训练等特点，将其应用于垃圾短信过滤中，并把分析结果及时反馈给在线过滤子系统，使得系统具有更好的自适应性。实验结果表明，该方法可有效地解决当前垃圾短信过滤系统中存在的问题。

Spam message self-adaptive filtering system based on Naive Bayes and support vector machine

With the development of the short message services,the characteristics and contents of the spam short Message are also changing constantly,the main problems that exist in the traditional short message filtering systems are that the characteristics and contents fail to be updated in time,which reduced the filter capability.This paper mainly utilized Na ve Bays advantage of rapid statistics classification and Support Vector Machine(SVM)incremental training characteristic in Spam Short Message filtering,and pr...