UrbanHubble: Location Prediction and Geo-Social Analytics in LBSN

  • Roland AssamEmail author
  • Simon Feiden
  • Thomas Seidl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9286)


Massive amounts of geo-social data is generated daily. In this paper, we propose UrbanHubble, a location-based predictive analytics tool that entails a broad range of state-of-the-art location prediction and recommendation algorithms. Besides, UrbanHubble consists of a visualization component that depicts the real-time complex interactions of users on a map, the evolution of friendships over time, and how friendship triggers mobility.


Matrix Factorization Kernel Density Estimation Collaborative Filter Location Prediction Recommendation Algorithm 
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.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.RWTH Aachen UniversityAachenGermany

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