Individual encounter prediction based on mobile internet record data

Qian LI; Hao JIANG; Jintao YANG

doi:10.11959/j.issn.1000-0801.2017249

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Individual encounter prediction based on mobile internet record data

research and development | 更新时间：2024-06-05

- Individual encounter prediction based on mobile internet record data
- Telecommunications Science Vol. 33, Issue 10, Pages: 115-123(2017)
- 作者机构：
- 作者简介：
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- DOI：10.11959/j.issn.1000-0801.2017249
  CLC： TP393
- Published Online：2017-10，
  
  Published：15 October 2017
- 稿件说明：
移动端阅览
Qian LI, Hao JIANG, Jintao YANG. Individual encounter prediction based on mobile internet record data[J]. Telecommunications science, 2017, 33(10): 115-123.
DOI：

Qian LI, Hao JIANG, Jintao YANG. Individual encounter prediction based on mobile internet record data[J]. Telecommunications science, 2017, 33(10): 115-123. DOI： 10.11959/j.issn.1000-0801.2017249.

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。

Abstract

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 internet 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.

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references

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