SWeMoF: A Semantic Framework to Discover Patterns in Learning Networks

Authors:
Marco Kalz;Niels Beekman;Anton Karsten;Diederik Oudshoorn;Peter Rosmalen;Jan Bruggen;Rob Koper
Affiliations:
Center for Learning Sciences and Technologies, Open University of the Netherlands, Heerlen, The Netherlands 6401;Faculty of Informatics, Open University of the Netherlands, Heerlen, The Netherlands 6401;Faculty of Informatics, Open University of the Netherlands, Heerlen, The Netherlands 6401;Faculty of Informatics, Open University of the Netherlands, Heerlen, The Netherlands 6401;Center for Learning Sciences and Technologies, Open University of the Netherlands, Heerlen, The Netherlands 6401;Center for Learning Sciences and Technologies, Open University of the Netherlands, Heerlen, The Netherlands 6401;Center for Learning Sciences and Technologies, Open University of the Netherlands, Heerlen, The Netherlands 6401
Venue:
EC-TEL '09 Proceedings of the 4th European Conference on Technology Enhanced Learning: Learning in the Synergy of Multiple Disciplines
Year:
2009

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Abstract

In this contribution we introduce SWeMoF, a semantic framework to discover patterns in learning networks and the blogosphere. Based on a description of the state of the art in data mining, text mining and blog mining we discuss the architecture of the Semantic Weblog Monitoring Framework (SWeMoF) and provide an outlook and an evaluation perspective for future research and development.