Design And Implementation Of User Close Degree Model For Caiyin Social Network Services

According to the rapid expansion of Internet technology, a variety of social network services come into people’s life in the field of computer games, music, reading and so on. However, those social network services have too much in common, sharing the same problems of dull users relationship and information overloading. In this way, people can not manage the relationship meticulousry, only using the same way. Therefore, social network service only means entertainment for people to kill time, failing to realize it’s real value of showing the same association between people in real world.As a new added-value telecommunication service, Caiyin also has a character which Internet services have in common. The content of a Caiyin is a character string with a length of45. Just like the state words in QQ and twitter, Caiyin will be spread at a high rate of speed in Internet. The SNS of Caiyin is a friendly environment for users of Caiyin service, where they can copy and comment on the Caiyins of their friends, and recommend their favourite Caryin to their friends.After the analysic for problems in SNS and characteristic of Caiyin service, Users Close Degree Model is required for analyzing users’ behavior with a number of data mining tools. The model will provide a good way to tell the differences in relationship between users in Caiyin service, using the calculated results of different kinds of degree including Basis Close Degree, Similarity Close Degree and Interaction Close Degree, based on the data of users’basic information and behavior information.This paper is divided into seven parts. The first part introduces the current situation of the research about people’s relationship in SNS, and recommend the Users Close Degree Model which will solve the problems in users’dull relationship and information overloading. The second part talks about some data mining technologies. The third part tells the data of users and contents in Caiyin service. The fourth part introduces a certain way to construct a data warehouse based on the data of users and contents. The fifth part gives a detail description about the User Close Degree Model which consists of Basis Close Degree, Similarity Close Degree and Interaction Close Degree. And some applications of combination these degrees are also be introduced. The sixth part talk about some ways to examine the model. The last part gives a summary for this paper.