Work in Progress: Identification of Inference Rules for a Semantic E-learning Brokerage Architecture

As more e-learning platforms are deployed there is a greater need of suitable intermediary systems that allow potential students to ease the searching and location of appropriate e-learning courses. Techniques and mechanisms that ensure that the time and efforts spent in discovering suitable courses is minimized need to be developed. Our work aims at contributing to the definition of such techniques and mechanisms by the identification of a semantic-based e-learning brokerage architecture that supports intelligent filtering of information. In particular, this paper focuses on the identification of logic rules required for preprocessing collected data in order to obtain significant information