Property-based collaborative filtering for health-aware recommender systems

Recommender systems aim at solving the problem of information overload by selecting items (commercial products, educational assets, TV programs, etc) that match the users´ interests and preferences. Recently, there have been approaches to drive the recommendations by the information stored in electronic health records, for which the traditional strategies applied in e-commerce, e-learning, entertainment and other areas have several pitfalls. We address those problems by introducing a filtering strategy centered on the properties that characterize the items and the users, which in turn serves to present the recommendations in a much more enticing manner.