Filling the Gaps: On the Completion of Sparse Call Detail Records for Mobility Analysis

Abstract : Call Detail Records (CDRs) have been widely used in the last decades for studying different aspects of human mobility. The accuracy of CDRs strongly depends on the user-network interaction frequency: hence, the temporal and spatial spar-sity that typically characterize CDR can introduce a bias in the mobility analysis. In this paper, we evaluate the bias induced by the use of CDRs for inferring important locations of mobile subscribers, as well as their complete trajectories. Besides, we propose a novel technique for estimating real human trajectories from sparse CDRs. Compared to previous solutions in the literature, our proposed technique reduces the error between real and estimated human trajectories and at the same time shortens the temporal period where users' locations remain undefined.
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Communication dans un congrès
Proceedings of the Eleventh ACM Workshop on Challenged Networks, Oct 2016, New York City, United States. pp.45 - 50, 2016
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Sahar Hoteit, Guangshuo Chen, Aline Carneiro Viana, Marco Fiore. Filling the Gaps: On the Completion of Sparse Call Detail Records for Mobility Analysis. Proceedings of the Eleventh ACM Workshop on Challenged Networks, Oct 2016, New York City, United States. pp.45 - 50, 2016. 〈hal-01448821〉

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