Human Mobility-Pattern Discovery and Next-Place Prediction from GPS Data

  • Faina Khoroshevsky
  • Boaz Lerner
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10183)


We provide a novel algorithm for the discovery of mobility patterns and prediction of users’ destination locations, both in terms of geographic coordinates and semantic meaning. We did not use any semantic data voluntarily provided by a user, and there was no sharing of data among the users. An advantage of our algorithm is that it allows a trade-off between prediction accuracy and information. Experimental validation was conducted on a GPS dataset collected in the Microsoft Research Asia GeoLife project by 168 users in a period of over five years.


GeoLife Human behavior Location extraction Mobility pattern Next place prediction Positioning technology Semantic information Stay point Trajectory data 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Ben-Gurion University of the NegevBeer-ShevaIsrael

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