Abstract
The booming development of wearable devices has created new opportunities and challenges for recommender system research. In fact, the relevance of a recommendation is largely affected by the user’s real-time requirements, and therefore understanding the precise user’s situation at recommendation time is pivotal. Wearable devices can contribute to provide this rich description of the user’s situation. In particular, in food recommender systems this set of user’s data can lead to novel research challenges that are illustrated in this paper.