Research And Application Of Data Mining Technology Used In The Analysis Of VIP User Behavior

With the development of information technology, the information systems of many industries have collected a huge amount of data these years. These data include a lot of information about the customers and increase exponentially. Thus, how to accurately find out useful knowledge and discover the implicit mode of the data timely can help the enterprises to formulate the strategies of market, to keep the former customers, to attract new customers and to take the preemptive opportunities. Based on the behavior of customers, this thesis analyses relative data of the enterprises users by adopting the method of data mining to discover the concealed law and mode. The analysis is based on the behavior of VIP customers of the operators and students who received a distance education.Because of the competition of the mobile communications markets increasing fiercely, VIP customers have become the focus of competition for the telecommunication business. How to attract and retain the most valuable VIP customers and develop the potential VIP customers has become the key of the competition. In this paper we used data mining methods to analyze the Network Data of VIP customers, find the behavior Of VIP customers, and make the right algorithms and models to provide the basis for Business providers to develop Marketing Strategy.In the light of distance education, distance education has been a focus of network research and application, as the development of Internet and Web technology. However, as distance education in recent days is one-system model, featuring its own system, the students have to receive the completely same learning passively. Thus, it doesn't reflect the advantages of characteristic education. In this thesis, considering the individual differences and emphasing on the desires and interests of the learners, we analyse the data of distance education system through the method of web data mining, which is based on the behavior of customers. We find out the characteristics of the behavior of the distance education learners to provide the basis for the learning environment of characteristic distance education and make the students learn in accordance of their aptitude which is necessary in distance education.