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Retrieving Points of Interest from Human Systematic Movements

  • Riccardo Guidotti
  • Anna Monreale
  • Salvatore Rinzivillo
  • Dino Pedreschi
  • Fosca Giannotti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8938)

Abstract

Human mobility analysis is emerging as a more and more fundamental task to deeply understand human behavior. In the last decade these kind of studies have become feasible thanks to the massive increase in availability of mobility data. A crucial point, for many mobility applications and analysis, is to extract interesting locations for people. In this paper, we propose a novel methodology to retrieve efficiently significant places of interest from movement data. Using car drivers’ systematic movements we mine everyday interesting locations, that is, places around which people life gravitates. The outcomes show the empirical evidence that these places capture nearly the whole mobility even though generated only from systematic movements abstractions.

Keywords

Recommendation System Systematic Movement Mobility Data Shopping Center Human Mobility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work has been partially supported by the European Commission under the FET-Open Project n. FP7-ICT-284715, ICON, and by the European Commission under the SMARTCITIES Project n. FP7-ICT-609042, PETRA.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Riccardo Guidotti
    • 1
    • 2
  • Anna Monreale
    • 1
    • 2
  • Salvatore Rinzivillo
    • 2
  • Dino Pedreschi
    • 1
  • Fosca Giannotti
    • 2
  1. 1.KDDLabUniversity of PisaPisaItaly
  2. 2.KDDLabISTI-CNRPisaItaly

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