基于手机上网记录数据的个体相遇预测

摘要

随着反映个体位置信息的数据大量涌现,人类移动行为的研究引起了业界学者的广泛关注.针对个体相遇预测问题,使用用户手机终端上网产生的会话数据进行分析.首先基于用户相遇关系进行复杂网络建模,然后分析了网络拓扑结构特征,同时引入了用户移动性特征和上网行为特征,构造基于随机森林的预测模型,进行个体相遇预测.实验结果表明,相比于传统的网络拓扑结构特征,通过引入用户移动性特征和上网行为特征,能够显著地提升预测性能.%Studies on human movement behavior have drawn much attention with the availability of unprecedented amount of records with high accuracy involving individuals' trajectories.The encounter prediction problem based on the session data generated by users' mobile terminal was studied when users accessed the intemet for data usage.Firstly,the network based on the encounter relations between users was constructed.Secondly,the network topology features were analyzed and user mobility characteristics and user internet behavior characteristics were introduced.Finally,the prediction model based on random forest was applied.The experimental results show that compared with the traditional network topology features,the prediction performance can be significantly improved by introducing the user mobility characteristics and user internet behavior characteristics.