Poster – Paper 578

Enhancing Categorization of Learning Resources in the DAtaset of Joint Educational Entities Carla Limongelli, Matteo Lombardi, Alessandro Marani and Davide Taibi Poster October 23, 2017, Poster and Demo Reception, 18:30-21:20 Festsaal 1 Download paper (preprint)

Abstract

The DAtaset of Joint Educational Entities (DAJEE) is a repository which hosts more than 20,000 educational resources crawled from the MOOC platform Coursera. The resources are divided per category according to the MOOC categorization on Coursera, which is, however, very shallow. This contribution focuses on a more meaningful categorization of the resources in DAJEE, tailored to their content. To achieve such goal, our approach enriches the resources in DAJEE with semantic entities by applying state-of-the-art semantic techniques. The result is a significant improvement of the categorization of the resources in DAJEE than the previous version.