Similarities detection between academic career content through the application of semantic technologies and data mining

Currently, Higher Education Institutions (IES) of Ecuador manage the information and contents of the subjects through a syllable system, whose contents are not normalized. The variety of formats and data models used by each IES, generates problems when carrying out processes, such as student mobility or difficulty in loan recognition tasks. To solve these problems, this project has been raised that through semantic technologies and text mining will try to identify similarities between different academic career content.