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A Tagging Recommender Service for Mobile Terminals

In: Information and Communication Technologies in Tourism 2013

Author

Listed:
  • Fernando A. Mikic Fonte

    (Universidade de Vigo)

  • Marta Rey López

    (Xunta de Galicia)

  • Juan C. Burguillo

    (Universidade de Vigo)

  • Ana Peleteiro

    (Universidade de Vigo)

  • Ana B. Barragáns Martínez

    (Centro Universitario de la Defensa Escuela Naval Militar)

Abstract

This paper introduces more Tourism, a hybrid recommendation platform that provides information about tourist resources depending on the user profile, location, schedule and the amount of time for visiting interest points isolated or combined in a route. This platform is enriched with several services, such as: mashups, socialization, and adaptive interfaces in order to enrich the users experience when visiting touristic attractions. The system is able to find touristic resources taking into account users’ likes, through the use of hybrid Content-based Filtering + Collaborative Filtering techniques combined with tagging and folksonomies. To our knowledge, this is the first recommendation service oriented to mobile terminals that use extensively the advantages of Web 2.0 for social collaborative tagging.

Suggested Citation

  • Fernando A. Mikic Fonte & Marta Rey López & Juan C. Burguillo & Ana Peleteiro & Ana B. Barragáns Martínez, 2013. "A Tagging Recommender Service for Mobile Terminals," Springer Books, in: Lorenzo Cantoni & Zheng (Phil) Xiang (ed.), Information and Communication Technologies in Tourism 2013, edition 127, pages 424-435, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-36309-2_36
    DOI: 10.1007/978-3-642-36309-2_36
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    Cited by:

    1. Theo Arentze & Astrid Kemperman & Petr Aksenov, 2018. "Estimating a latent-class user model for travel recommender systems," Information Technology & Tourism, Springer, vol. 19(1), pages 61-82, June.

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