Conference Papers Year : 2017

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

Fichier principal
Vignette du fichier
main_after_final.pdf (477.22 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01448822 , version 1 (29-01-2017)

Identifiers

  • HAL Id : hal-01448822 , version 1

Cite

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⟩
162 View
220 Download

Share

More