Application Of Data Mining In Predication System Of Losing High-Value Customers Of China Netcom

With the telecommunication system reform development and our entrance of WTO, the competition of telecommunication operation is becoming fiercer. Compared with other industry, the mobile telecommunication operation has more data of customers. Who can mine and analyze the knowledge contained in the data correctly will offer product and service to customer better and find more opportunities, thus win the competition. Our domestic research on this field is still at infancy, companies abroad have already been superior to mine greatly. So, there is important practical value in the research on data mining of our telecommunication industry.This thesis mainly researches on our mobile telecommunication operation how to launch and use data mining to raise its competitive advantage. This thesis has not discussed much on data mining theory and the modeling method, etc. Nor has the construction of data warehouse. We put focal point on the choice and design that the model of data mining, on the basis of the already studies of abroad and the actual needs of Beijing China net communication company. Put real data on Decision Trees or regression model, and SAS Enterprise Miner was used to test and appraise these models.The main contribution of this thesis are follows:1. Described the actuality of high-value customers losing predication of China Netcom. Set up the research object, method and effect to be achieved.2. Described how to analyze and make the predication model for high-value customers losing. 3. Introduced Decision Trees and Regression methods to obtain two predication models, and compared them.4. The actual effects of custom losing prediction system in China Netcom.