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Context-Aware Points of Interest Suggestion with Dynamic Weather Data Management

In: Information and Communication Technologies in Tourism 2014

Author

Listed:
  • Matthias Braunhofer

    (Free University of Bozen)

  • Mehdi Elahi

    (Free University of Bozen)

  • Francesco Ricci

    (Free University of Bozen)

  • Thomas Schievenin

    (Free University of Bozen)

Abstract

Weather plays an important role in tourists’ decision-making and, for instance, some places or activities must not be even suggested under dangerous weather conditions. In this paper we present a context-aware recommender system, named STS, that computes recommendations suited for the weather conditions at the recommended places of interest (POI) by exploiting a novel model-based context-aware recommendation technique. In a live user study we have compared the performance of the system with a variant that does not exploit weather data when generating recommendations. The results of our experiment have shown that the proposed approach obtains a higher perceived recommendation quality and choice satisfaction.

Suggested Citation

  • Matthias Braunhofer & Mehdi Elahi & Francesco Ricci & Thomas Schievenin, 2013. "Context-Aware Points of Interest Suggestion with Dynamic Weather Data Management," Springer Books, in: Zheng Xiang & Iis Tussyadiah (ed.), Information and Communication Technologies in Tourism 2014, edition 127, pages 87-100, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-03973-2_7
    DOI: 10.1007/978-3-319-03973-2_7
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    Citations

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    Cited by:

    1. Thuy Ngoc Nguyen & Francesco Ricci, 2018. "A chat-based group recommender system for tourism," Information Technology & Tourism, Springer, vol. 18(1), pages 5-28, April.
    2. Matthias Braunhofer & Francesco Ricci, 2017. "Selective contextual information acquisition in travel recommender systems," Information Technology & Tourism, Springer, vol. 17(1), pages 5-29, March.
    3. Matthias Braunhofer & Francesco Ricci, 0. "Selective contextual information acquisition in travel recommender systems," Information Technology & Tourism, Springer, vol. 0, pages 1-25.

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