A two-dimensional Apriori based user behavior prediction algorithm in mobile social environment

According to the group, interactive and real-time characteristics of mobile social environment, a novel user behavior prediction algorithm in mobile social environment is proposed in this paper. In this algorithm, firstly, a coding based two-dimensional Apriori method is presented to analyze user service behaviors: on one hand, the correlation analysis of a user behavior history is performed; on the other hand, an effectiveness factor formula is adopted to separate n correlated users of a person from its friend circle and get their effectiveness factors, and then the correlation analysis between the person and each correlated user is made. Secondly, an improved optimal weighted fusion method based on effectiveness factor is proposed to integrate n+1 correlation analysis results. By analyzing the history information of user service behaviors, the algorithm can predict user service behaviors in the next moment and provide joint service recommendations for users accurately. Finally, simulation results demonstrate the efficiency and accuracy of the proposed algorithm.