we proposed a centrality prediction method based on K-order Markov chains to solve the problem of centrality prediction in mobile social networks. In the real mobile social data set, the information entropy of the computation is used to analyze the past and future regularity of the node's centrality, and the predictability of the node's centrality is verified. Using the historical information of the center of the node, the state probability matrix is constructed to predict the future central value of the node. Through the analysis of the error between real value and predicted value, we evaluate the performance of the prediction methods. The results show that the prediction model based on the K-order Markov chain when K=2 is not optimized on the individual on the MIT dataset and the Infocom 06 data set, but on the whole to achieve the optimization.

Filename	Size	Update
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