ON THE VALUE OF PURPOSE-ORIENTATION AND FOCUS ON LOCALS IN RECOMMENDING LEISURE ACTIVITIES

Authors

  • BEATRICE VALERI DISI, University of Trento via Sommarive 9, 38123 Povo, Trento, Italy
  • FABIO CASATI DISI, University of Trento via Sommarive 9, 38123 Povo, Trento, Italy
  • FLORIAN DANIEL DEIB, Politecnico di Milano via Ponzio 34/5, 20133 Milano, Italy

Keywords:

Recommender systems, data collection, mobile recommendations, restaurants, TripAdvisor

Abstract

Recommender systems are omnipresent today, especially on the Web, and the quality of their recommendations is crucial for user satisfaction. Unlike most works on the topic, in this article we do not focus on the algorithmic side of the problem (i.e., searching for the algorithm that better learns from the collected user feedback) and instead study the importance of the data in input to the algorithms, identifying the information that should be collected from users to build better recommendations. We study restaurant recommendations for locals and show that ne-tuned data and state-of-the-art algorithms can outperform the leading recommendation service, TripAdvisor. The ndings make a case for better-thought and purpose-tailored data collection techniques.

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Published

2016-10-13

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Section

Articles