Differentially private publication of location entropy

@article{To2016DifferentiallyPP,
  title={Differentially private publication of location entropy},
  author={Hien To and Kien Nguyen and C. Shahabi},
  journal={Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems},
  year={2016}
}
  • Hien To, Kien Nguyen, C. Shahabi
  • Published 2016
  • Computer Science, Mathematics
  • Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Location entropy (LE) is a popular metric for measuring the popularity of various locations (e.g., points-of-interest). Unlike other metrics computed from only the number of (unique) visits to a location, namely frequency, LE also captures the diversity of the users' visits, and is thus more accurate than other metrics. Current solutions for computing LE require full access to the past visits of users to locations, which poses privacy threats. This paper discusses, for the first time, the… Expand
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Location entropy (LE) is an eminent metric for measuring the popularity of various locations (e.g., points-of-interest). It is used in numerous applications in geo-marketing, crime analysis,Expand
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