Similarity of Mobile Users Based on Sparse Location History

  • Pasi FräntiEmail author
  • Radu Mariescu-Istodor
  • Karol Waga
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10841)


We propose a method to measure similarity of users based on their sparse location history such as geo-tagged photos or check-in activity of user. The method is useful when complete movement trajectories are not available. We map each activity point into the nearest location in a predefined set of fixed places. The problem is then formulated as histogram comparison. We compare the performance of similarity measures such as L1, L2, L, ChiSquared, Bhattacharyya and Kullback and Leibler divergence using both crisp and fuzzy histograms. Results show that user can be recognized with fair accuracy, and that all similarity measures are suitable except L2 and L, which perform poorly.


User similarity Mobile activity GPS data analysis Histogram matching Fuzzy pattern recognition Location-based services 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Pasi Fränti
    • 1
    Email author
  • Radu Mariescu-Istodor
    • 1
  • Karol Waga
    • 1
  1. 1.School of ComputingUniversity of Eastern FinlandJoensuuFinland

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