ChemRecSys (Chemical Compounds Recommender System) is a system for recommending Chemical Compounds, integrating collaborative-filtering algorithms for implicit feedback (Alternating Least Squares (ALS) and Bayesian Personalized Ranking(BPR)), a content-based algorithm based on the semantic similarity between the Chemical Compounds in the ChEBI ontology (ONTO), and a hybrid algorithm.
Team: Márcia Barros; André Moitinho (CENTRA-SIM/FCUL); Francisco M. Couto