作　　者： ; ;

机构地区： 华南理工大学计算机科学与工程学院

出　　处： 《计算机应用》 2007年第1期221-224,共4页

摘　　要： 提出了一种分布式的垃圾短信过滤系统,它适合于移动网络,具有自学习能力,能够及时发现垃圾信息源,有效的过滤垃圾短信。在传统以词为属性的贝叶斯过滤算法的基础上,加入了规则和长度信息,利用互信息减小单词属性的个数。实验表明,它在短信过滤方面具有空间占用小和性能更好的特点,适合在移动电话上使用。同时还提出了一种垃圾短信发送者的可能性排名的方法。 This paper introduced a distributed Short Message Service （SMS） filtering system which was applicable on mobile network. This system has self-learning and knowledge updating capability and it can find junk SMS sender with a proper high credibility. The main algorithm used in this system is the Nave Bayesian classification algorithm. Some attributes such as the length of the SMS and rules found by statistics are added to attribute set, and experiments show that it results in a better performance than the traditional word based Bayesian approach. This paper also provided an approach to rank the suspicious SMS senders on their probabilities to be real junk SMS senders according to some measures.

关 键 词： 移动计算 垃圾短信 短信过滤 朴素贝叶斯

领　　域： [电子电信] [电子电信] [自动化与计算机技术] [自动化与计算机技术]