, Volume 21, Issue 1, pp 33–55 | Cite as

Exploiting location-aware social networks for efficient spatial query processing

  • Liang Tang
  • Haiquan Chen
  • Wei-Shinn Ku
  • Min-Te Sun


In this paper, we introduce two watchtower-based parameter-tunable frameworks for efficient spatial processing with sparse distributions of Points of Interest (POIs) by exploiting mobile users’ check-in data collected from the location-aware social networks. In our proposed frameworks, the network traversal can terminate earlier by retrieving the distance information stored in watchtowers. More important, by observing that people’s movement often exhibits a strong spatial pattern, we employ Bayesian Information Criterion-based cluster analysis to model mobile users’ check-in data as a mixture of 2-dimensional Gaussian distributions, where each cluster corresponds to a geographical hot zone. Afterwards, POI watchtowers are established in the hot zones and non-hot zones discriminatorily. Moreover, we discuss the optimal watchtower deployment mechanism in order to achieve a desired balance between the off-line pre-computation cost and the on-line query efficiency. Finally, the superiority of our solutions over the state-of-the-art approaches is demonstrated using the real data collected from Gowalla with large-scale road networks.


Advanced traveler information systems Query processing Location-based services 



This research has been funded in part by the National Science Foundation grant CNS-0917137 and the Faculty Scholarship award from Valdosta State University.


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Liang Tang
    • 1
  • Haiquan Chen
    • 2
  • Wei-Shinn Ku
    • 1
  • Min-Te Sun
    • 3
  1. 1.Department of Computer Science and Software EngineeringAuburn UniversityAuburnUSA
  2. 2.Department of Mathematics and Computer ScienceValdosta State UniversityValdostaUSA
  3. 3.Department of Computer Science and Information EngineeringNational Central UniversityTaoyuanTaiwan

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