Research on junk SMS filtering system on mobile environment
移动环境下的垃圾短信过滤系统的研究

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.