A federated recommender system for online learning environments

Authors:
Lei Zhou;Sandy El Helou;Laurent Moccozet;Laurent Opprecht;Omar Benkacem;Christophe Salzmann;Denis Gillet
Affiliations:
Tongji University, Shanghai, China;Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland;University of Geneva (UNIGE), Geneva, Switzerland;University of Geneva (UNIGE), Geneva, Switzerland;University of Geneva (UNIGE), Geneva, Switzerland;Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland;Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Venue:
ICWL'12 Proceedings of the 11th international conference on Advances in Web-Based Learning
Year:
2012

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Abstract

From e-commerce to social networking sites, recommender systems are gaining more and more interest. They provide connections, news, resources, or products of interest. This paper presents a federated recommender system, which exploits data from different online learning platforms and delivers personalized recommendation. The underlying educational objective is to enable academic institutions to provide a Web 2.0 dashboard bringing together open resources from the Cloud and proprietary content from in-house learning management systems. The paper describes the main aspects of the federated recommender system, including its adopted architecture, the common data model used to harvest the different learning platforms, the recommendation algorithm, as well as the recommendation display widget.