PRED: Periodic region detection for mobility modeling of social media users

Quan Yuan, Wei Zhang, Chao Zhang, Xinhe Geng, Gao Cong, Jiawei Han

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

Abstract

The availability of massive geo-annotated social media data sheds light on studying human mobility patterns. Among them, periodic pattern, i.e., an individual visiting a geographical region with some specific time interval, has been recognized as one of the most important. Mining periodic patterns has a variety of applications, such as location prediction, anomaly detection, and location- and time-aware recommendation. However, it is a challenging task: the regions of a person and the periods of each region are both unknown. The interdependency between them makes the task even harder. Hence, existing methods are far from satisfactory for detecting periodic patterns from the low-sampling and noisy social media data. We propose a Bayesian non-parametric model, named Periodic REgion Detection (PRED), to discover periodic mobility patterns by jointly modeling the geographical and temporal information. Our method differs from previous studies in that it is non-parametric and thus does not require priori knowledge about an individual's mobility (e.g., number of regions, period length, region size). Meanwhile, it models the time gap between two consecutive records rather than the exact visit time, making it less sensitive to data noise. Extensive experimental results on both synthetic and realworld datasets show that PRED outperforms the state-of-the-art methods significantly in four tasks: periodic region discovery, outlier movement finding, period detection, and location prediction.

Original languageEnglish (US)
Title of host publicationWSDM 2017 - Proceedings of the 10th ACM International Conference on Web Search and Data Mining
PublisherAssociation for Computing Machinery, Inc
Pages263-272
Number of pages10
ISBN (Electronic)9781450346757
DOIs
StatePublished - Feb 2 2017
Event10th ACM International Conference on Web Search and Data Mining, WSDM 2017 - Cambridge, United Kingdom
Duration: Feb 6 2017Feb 10 2017

Publication series

NameWSDM 2017 - Proceedings of the 10th ACM International Conference on Web Search and Data Mining

Other

Other10th ACM International Conference on Web Search and Data Mining, WSDM 2017
CountryUnited Kingdom
CityCambridge
Period2/6/172/10/17

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Computer Networks and Communications
  • Software

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