Abstract：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.
卢扬, 赵志丹, 蔡世民. 基于移动终端上网数据的移动模式分析及轨迹预测[J]. 复杂系统与复杂性科学, 2015, 12(2): 53-59.
LU Yang, ZHAO Zhidan, CAI Shimin. Mobility Pattern Analysis and Trajectory Prediction Using Mobile GPRS Data[J]. Complex Systems and Complexity Science, 2015, 12(2): 53-59.
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