In this article, we analyzed users′ mobility patterns and proposed several predictors to solve the next location prediction problem with users′ mobile GPRS data. It is found that individual′s mobile behaviors are bursting, heterogeneous, weakly regular in temporal-spacial aspect, and individuals tend to stay in the same location in a short interval time. Furthermore, based on these empirical results, a blending model is developed to improve the prediction accuracy, overcomingall models with standalone feature.
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