Mobile music recommendations for runners based on location and emotions: The DJ-Running system

Music can produce a positive effect in runners' motivation and performance. Neverthe-less, these effects vary depending on the user's location, the emotions that she/he feels at each moment or the type of training session. In this paper, a context and emotion-aware system for the recommendation and playing of Spotify songs is presented. It consists in a location-based mobile application that interacts with a novel emotional wearable and a recommendation service that predicts the next song to be recommended. These predictions are performed by an intelligent system that combines artificial intelligent techniques with geodata and emotionally-annotated music. A wide variety of location-based services and music services available in Internet have been integrated into the recommender in order to support the decision-making process in a real environment. The final solution has been customized to be tested in the city of Zaragoza. (C) 2020 Elsevier B.V. All rights reserved.