A Pre-recognition Method For Junk Message Filtering Based On Data Mining

With the rapid development of wireless communications services, SMS service become more and more important in everyday life.Meanwhile, large junk message emerge with the short message service development, it disturb the daily life of mobilephone users.Junk message has strong gender of concealment, it’s content,written form and the frequency of message sending kept changing, so it is very difficult to find out. Depends on tranditional method of monitoring key words and traffic could not meet the operator’s requirments.Nowadays the text analysis,black or white list filtering and machine learning are mainstream methods of junk message filtering, compare with these methods of analysing the message content, this paper select a new way which based on decision tree, through customer attribute, customer behavior and other dimension to construct the model, then find out the telephone number which send the junk message, formed a high risk telephone number list. The result show that the method can effectively identify the telephone number which send out the junk messages, this model will be beneficial to supporting the monitoring system.This article the first chapter introduce the background of junk message filtering and the main methord to filter the junk message; The second and third chapter introduce the algorithm and the process of prepare data; The fourth chapter introduce the principle of module and how to construct it;The fifth chapter is mainly analysing the result, estimate the efficiency and veracity; The last chapter make a summary,point out the fault of algorithm and prospect for the future.