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With the rapid development of the telecommunications industry, in addition to traditional services such as broadband telecommunications business, telecommunications access to the 3G licenses after the company received another leap in development opportunities, and bring development opportunities that the mobile telecommunications business, into the 3G era, mobile service carriers and makes three Telecom operators to stand in the starting line, and mobile value-added mobile services business is one of the most important growth point, how effective recommended mobile value-added services to customers, become a topic worthy of study, and telecommunications as an important data mining research of field, making the data mining application in the more mature the industry.This paper studies on the analysis of customer behavior to drive the development of mobile value-added services the actual demand, the establishment of mobile value-added business model, and to assess the model, make recommendations to the customers to order services, and secondly, by building models data mining, association rules in knowledge have been studied in the detailed analysis of the advantages and disadvantages of the association rules algorithm, the Apriori algorithm has discussed some of its deficiencies, and then made more efficient for the telecommunications industry relational database algorithm, and validated by data mining software, mobile value-added services for telecommunications customers for data mining, by evaluating the function node, the formation of knowledge.This modeling process is using CRISP-DM data mining process of standardized, it is widely recognized, used one of the most extensive in methodology, and a exemplification of the business issues and data mining techniques combined of well.
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