Recommendations on the Move

  • Alicia Rodríguez-CarriónEmail author
  • Celeste Campo
  • Carlos García-Rubio
Part of the Intelligent Systems Reference Library book series (ISRL, volume 32)


Recommender systems can take advantage of the user’s current location in order to improve the recommendations about places the user may be interested in. Taking a step further, these suggestions could be based not only on the user’s current location, but also on the places where the user is supposed to be in the near future, so the recommended locations would be on the path the user is going to follow. In order to do that we need some location prediction algorithms so that we can get those future locations. In this chapter we explain how to use the algorithms belonging to LZ family (LZ, LeZi Update and Active LeZi) as recommender engines, and we propose some ways of using these algorithms in places where the user has not been before or how to take advantage of the social knowledge about certain place so as to make these recommendations richer. Finally we show a prototype implementation of a recommender system for touristic places made up of these LZ predictors.


Global Position System Mobile Phone Recommender System Current Location Prediction 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-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Alicia Rodríguez-Carrión
    • 1
    Email author
  • Celeste Campo
    • 1
  • Carlos García-Rubio
    • 1
  1. 1.Department of Telematic EngineeringUniversity Carlos III of MadridLeganés, MadridSpain

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