Building an intelligent system for answering specialized questions about COVID-19

The paper discusses the design and implementation process of an intelligent system for answering specialized questions about COVID-19. The system is based on deep learning and transfer learning techniques and uses the popular CORD-19 dataset as a source of scientific knowledge about the problem domain. The experiments performed with the pilot version of the system are presented and the obtained results are analyzed. Conclusions are formulated about the applicability and the opportunities for improvement of the proposed approach.