%0 Journal Article
%A WANG Min
%A ZHANG Hui
%T Optimal Correlation Prediction of User Behaviors Based on Mobile Social Environment
%D 2017
%R 10.13190/j.jbupt.2017-141
%J Journal of Beijing University of Posts and Telecommunications
%P 50-56
%V 40
%N 6
%X A multiple analysis and optimal prediction algorithm of user behaviors based on mobile social environment is proposed. First, for each social group of a target user, an optimization model based on representativeness degree is formulated to select the most representative correlated user from this social group for analyzing the service behaviors of target user caused by the corresponding social attribute; particularly, the representativeness degree consists of Kendall coefficient based similarity degree and interaction statistics based interaction degree. Second, by using Apriori theory, the correlation analyses for target user and its most representative correlated users are performed respectively, and then a least-square model based weighted fusion method is presented to integrate the above correlation analysis results optimally and predict user next behaviors accurately. Extensive simulation results verify the effectiveness of proposed algorithm.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2017-141