An improved Apriori–based algorithm for friends recommendation in microblog

Summary With the rapid development of Internet, the world has come into a new era of network interaction. Internet development in China makes various kinds of software available to users, by which relatives, close friends, and partners can achieve real-time interactions. It is acknowledged that the recommended issues and persons are the most important parts for user experience. This study concentrates on how to provide a recommendation for users with a common interest in Microblog. We first illustrate some recommended algorithms based on data mining, and the implementation process of friend-recommended system is then stated. After that, by integrating the characteristics of the user information, the forwarding and comments on information to associated users, we present an improved Apriori–based algorithm to rank the recommended information with confidence interval. Simulation results demonstrate the superiority and efficiency of our method.

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