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A Novel User Behavior Prediction Algorithm in Mobile Social Environment

Hui Zhang,
Min Wang,
Longxiang Yang,
Hongbo Zhu,


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. First, a coding based two-dimensional Apriori method is presented to improve the efficiency of user behavior analysis. Furthermore, in order to comprehensively analyze user behaviors, on one hand, the correlation analysis based on behavior history of a target user is performed; on the other hand, an effectiveness factor is formulated to obtain the optimal correlation set of target user from its friend circle, and then the correlation analysis between the target user and each correlated user from its optimal correlation set is performed. Finally, for integrating the above correlation analysis results, an improved optimal weighted fusion method based on effectiveness factors is presented, so as to achieve accurate prediction of user service behaviors. Extensive simulations results show that the proposed algorithm outperforms several related algorithms in terms of prediction efficiency and accuracy.

Citation Format:
Hui Zhang, Min Wang, Longxiang Yang, Hongbo Zhu, "A Novel User Behavior Prediction Algorithm in Mobile Social Environment," Journal of Internet Technology, vol. 19, no. 4 , pp. 1023-1030, Jul. 2018.

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