Towards an Adaptive Completion of Sparse Call Detail Records for Mobility Analysis

Abstract : Call Detail Records (CDRs) are a primary source of whereabouts in the study of multiple mobility-related aspects. However, the spatiotemporal sparsity of CDRs often limits their utility in terms of the dependability of results. In this paper, driven by real-world data across a large population, we propose two approaches for completing CDRs adaptively, to reduce the sparsity and mitigate the problems the latter raises. Owing to high-precision sampling, the comparative evaluation shows that our approaches outperform the legacy solution in the literature in terms of the combination of accuracy and temporal coverage. Also, we reveal those important factors for completing sparse CDR data, which sheds lights on the design of similar approaches.
Keywords : Location Boundaries
Type de document :
Communication dans un congrès
Workshop on Data Analytics for Mobile Networking, Mar 2017, Kona, United States
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https://hal.inria.fr/hal-01448822
Contributeur : Guangshuo Chen <>
Soumis le : dimanche 29 janvier 2017 - 12:19:34
Dernière modification le : mardi 9 janvier 2018 - 13:46:49
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  • HAL Id : hal-01448822, version 1

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Guangshuo Chen, Aline Carneiro Viana, Carlos Sarraute. Towards an Adaptive Completion of Sparse Call Detail Records for Mobility Analysis. Workshop on Data Analytics for Mobile Networking, Mar 2017, Kona, United States. 〈hal-01448822〉

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