How Random Walks Can Help Tourism

  • Claudio Lucchese
  • Raffaele Perego
  • Fabrizio Silvestri
  • Hossein Vahabi
  • Rossano Venturini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7224)

Abstract

On-line photo sharing services allow users to share their touristic experiences. Tourists can publish photos of interesting locations or monuments visited, and they can also share comments, annotations, and even the GPS traces of their visits. By analyzing such data, it is possible to turn colorful photos into metadata-rich trajectories through the points of interest present in a city.

In this paper we propose a novel algorithm for the interactive generation of personalized recommendations of touristic places of interest based on the knowledge mined from photo albums and Wikipedia. The distinguishing features of our approach are multiple. First, the underlying recommendation model is built fully automatically in an unsupervised way and it can be easily extended with heterogeneous sources of information. Moreover, recommendations are personalized according to the places previously visited by the user. Finally, such personalized recommendations can be generated very efficiently even on-line from a mobile device.

Keywords

Random Walk Recommender System Normalize Precision Recommendation Algorithm Subway Station 
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

  • Claudio Lucchese
    • 1
  • Raffaele Perego
    • 1
  • Fabrizio Silvestri
    • 1
  • Hossein Vahabi
    • 1
    • 2
  • Rossano Venturini
    • 1
  1. 1.ISTI-CNRPisaItaly
  2. 2.IMTLuccaItaly

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