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Mining Foursquare User Check-in Habit Based on Historical Check-in Records

  • Yan Zhuang
  • Simon FongEmail author
  • Meng Yuan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 393)

Abstract

Location prediction is the latest development direction in these year. This paper proposes a new method which does not need each individual history path and ID to match his/her history path with prediction path database to predict the user’s next location. In this experiment, we used two pair of coordinates to give a prediction. It’s based on the foursquare dataset. And through changing the factors that affect the location prediction, like length and time, in the general experiment, the accuracy of the prediction will be enhanced.

Keywords

Data mining Next location prediction Foursqure 

Notes

Acknowledgments

The authors of this paper are thankful to the financial supports of the grant offered with code: MYRG2015-00024, called “Building Sustainable Knowledge Networks through Online Communities” by RDAO, University of Macau.

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Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  1. 1.Department of Computer and Information ScienceUniversity of MacauTaipaMacau SAR

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