Similarity detection among academic contents through semantic technologies and text mining

Nowadays, the information of university courses is managed by means of syllabus based systems, this is the case of Ecuadorian Higher Education Institutions (IES for its Spanish acronym). However, the syllabus structure is not normalized among all universities, since there is a wide variety of formats and data models used for each IES which naturally, affects academic processes such as the students mobility or credits validation between IES. We have addressed these issues by presenting a proposal based on semantic technologies and text mining methods whose goal is to identify similarities among academic contents.