Choice-based recommender systems

Choice-based models are proposed to overcome some of the limitations found in traditional rating-based strategies. The new approach is grounded on decision-making paradigms, such as choice and utility theories. Specically, random utility models were applied in a recommendation problem. Prediction accuracy was compared with state-of-art rating- based algorithms in a gastronomy dataset. The results show the superior performance of choice-based models, which may suggest that real choices could bring more predictive power than ratings.