Individual Trajectory Reconstruction from Mobile Network Data

Abstract : Mobile phone datasets are a primary source of positioning information for human mobility studies across many disciplines. They provide individual trajectory footprints in the form of geo-referenced and time-stamped events recorded in the mobile network. The quality of the mobility information in mobile phone datasets depends on the nature of the network infrastructure and on the frequency of its interactions with mobile devices. Typically, geographical deployments of cellular networks are far from uniform, and the events triggered by each mobile device are sparse and irregular in time. As a result, individual trajectories inferred from mobile network data are often substantially incomplete.
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Contributor : Guangshuo Chen <>
Submitted on : Monday, January 8, 2018 - 9:17:40 AM
Last modification on : Thursday, July 11, 2019 - 11:14:07 AM
Long-term archiving on : Wednesday, May 23, 2018 - 2:56:42 PM


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  • HAL Id : hal-01675570, version 1


Guangshuo Chen, Sahar Hoteit, Aline Carneiro Viana, Marco Fiore, Carlos Sarraute. Individual Trajectory Reconstruction from Mobile Network Data. [Technical Report] RT-0495, INRIA Saclay - Ile-de-France. 2018, pp.1-23. ⟨hal-01675570v1⟩



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