Title: Biomedical Relation Extraction with Knowledge Graph-based Recommendations
Speaker: Diana Sousa, LASIGE/DI-FCUL
Date: March 10, 12h
Where: Room C6.3.27
Abstract: Biomedical Relation Extraction (RE) systems identify and classify relations between biomedical entities to enhance our knowledge of biological and medical processes. Most state-of-the-art systems use deep learning approaches, mainly to target relations between entities of the same type, such as proteins or pharmacological substances. However, these systems are mostly restricted to what they directly identify on the text and ignore specialized domain knowledge bases, such as ontologies, that formalize and integrate biomedical information typically structured as direct acyclic graphs. On the other hand, Knowledge Graph (KG)-based recommendation systems already showed the importance of integrating KGs to add additional features to items. Typical systems have users as people and items that can range from movies to books, which people saw or read and classified according to their satisfaction rate. In this seminar I will present an approach to integrate KGs into biomedical RE through a recommendation model to further improve their range of action.