Modeling Fine-Grained Human Mobility on Cellular Networks

Zhihan Fang, Guang Wang, Desheng Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Cellular network data has been proved as one of the most promising ways to understand large-scale human mobility due to its high penetration of cellphones and low collection cost. Most existing mobility models driven by cellular network data are based on either CDR (Call Detail Records) or data connection records. However, estimated mobility is biased with coarse granularities due to the insufficient data quality. Mobility modeling on cellular networks always suffer from the sparse spatial-temporal observations since user locations are recorded with cellphone activities. In this paper, to solve the issue, we design a system named FineCell to model fine-grained human mobility based on sparse cellular network data. The key challenge we address in FineCell is to achieve fine-grained mobility modeling with sparse cellular network data. In contrast to the existing works on human mobility, the novelty of the FineCell is to infer missing spatial and temporal observations caused by sensing gaps in cellular networks. More importantly, we evaluate FineCell with large-scale fine-grained ground truth data from the same cellular network. The evaluation results show FineCell achieve 9.8% lower error compared with state-of-the-art models.

Original languageEnglish (US)
Title of host publicationThe Web Conference 2020 - Companion of the World Wide Web Conference, WWW 2020
PublisherAssociation for Computing Machinery
Pages35-37
Number of pages3
ISBN (Electronic)9781450370240
DOIs
StatePublished - Apr 20 2020
Event29th International World Wide Web Conference, WWW 2020 - Taipei, Taiwan, Province of China
Duration: Apr 20 2020Apr 24 2020

Publication series

NameThe Web Conference 2020 - Companion of the World Wide Web Conference, WWW 2020

Conference

Conference29th International World Wide Web Conference, WWW 2020
Country/TerritoryTaiwan, Province of China
CityTaipei
Period4/20/204/24/20

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

Keywords

  • Fine Grained
  • Human Mobility
  • Location Inference

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