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User Personality and the New User Problem in a Context-Aware Point of Interest Recommender System

In: Information and Communication Technologies in Tourism 2015

Author

Listed:
  • Matthias Braunhofer

    (Free University of Bozen - Bolzano)

  • Mehdi Elahi

    (Free University of Bozen - Bolzano)

  • Francesco Ricci

    (Free University of Bozen - Bolzano)

Abstract

The new user problem is an important and challenging issue that Context-Aware Recommender Systems (CARSs) must deal with, especially in the early stage of their deployment. It occurs when a new user is added to the system and there is not enough information about the user’s preferences in order to compute appropriate recommendations. It is common to address this problem in the recommendation algorithm, by using demographic attributes such as age, gender, and occupation, which are easy to collect and are reasonably good predictors of the user preferences. However, as we show here, user’s personality provides even better information for generating context-aware recommendations for places of interest (POI), and it is still easy to assess with a simple questionnaire. In our study, using a rating data set collected by a mobile app called STS (South Tyrol Suggests), we have found that by considering the user personality the system can better rank the recommendations for the new users.

Suggested Citation

  • Matthias Braunhofer & Mehdi Elahi & Francesco Ricci, 2015. "User Personality and the New User Problem in a Context-Aware Point of Interest Recommender System," Springer Books, in: Iis Tussyadiah & Alessandro Inversini (ed.), Information and Communication Technologies in Tourism 2015, edition 127, pages 537-549, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-14343-9_39
    DOI: 10.1007/978-3-319-14343-9_39
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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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