A Novel User Mobility Prediction Scheme based on the Weighted Markov Chain Model.

Recently, location-based service has become a hot research topic. Mobile communication data records abundant information about users' temporal and spatial characteristics. By modeling the users' mobility based on mobile communication data, this can assist to understand human user patterns more accurately and deeply. Initially, this paper introduces three mainstream algorithms for user mobility modeling. Then this paper proposes a novel Markov chain based user mobility prediction scheme. The proposed scheme is implemented through four stages, including time and space division, Markov property examination, transition probability matrix calculation, Markov model weighting. Experimental results show that the proposed scheme can achieve higher accuracy compared with the traditional algorithms.