Interdependence and predictability of human mobility and social interactions
Interdependence and predictability of human mobility and social interactions
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DOI：
10.1016/j.pmcj.2013.07.008
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发表时间：
2013-12-01
影响因子：
4.3
通讯作者：
Musolesi, Mirco
中科院分区：
文献类型：
--
作者：
De Domenico, Manlio;Lima, Antonio;Musolesi, Mirco
此前的研究表明，不同地理尺度下的人类移动在一定程度上是可预测的。现有的预测技术仅利用该人的过去历史作为预测器的输入。在本文中，我们表明，通过多元非线性时间序列预测技术，可以通过考虑朋友、人或更一般实体的移动以及相关移动模式（即以高互信息为特征）作为输入来提高预测准确性。最后，我们在诺基亚移动数据挑战赛和 Cabspotting 数据集上评估了所提出的技术。 (C) 2013 Elsevier B.V. 保留所有权利。
Previous studies have shown that human movement is predictable to a certain extent at different geographic scales. The existing prediction techniques exploit only the past history of the person taken into consideration as input of the predictors.In this paper, we show that by means of multivariate nonlinear time series prediction techniques it is possible to increase the forecasting accuracy by considering movements of friends, people, or more in general entities, with correlated mobility patterns (i.e., characterised by high mutual information) as inputs. Finally, we evaluate the proposed techniques on the Nokia Mobile Data Challenge and Cabspotting datasets. (C) 2013 Elsevier B.V. All rights reserved.