This paper presents a semantic personalized recommender system for biomedical ontologies. To do this, we design and implement a semantic repository of biomedical ontologies, containing metadata associated with each biomedical ontology. The knowledge stored in the metadata of the semantic repository is used for the recommender system, in order to give prioritized recommendations of the different biomedical ontologies that meet certain search criteria. The proposed recommender also considers hybridization, considering the calibration of the impact generated by two aspects: customization (adaptability) for each user, and the quality evaluation of each ontology to recommend.
['Jose Aguilar', 'Junior Altamiranda', 'Omar Portilla']
Hybrid recommender system of biomedical ontologies