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Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/2003

Title: SWeMoF: A semantic framework to discover patterns in learning networks
Authors: Kalz, Marco
Beekman, Niels
Karsten, Anton
Oudshoorn, Diederik
Van Rosmalen, Peter
Van Bruggen, Jan
Koper, Rob
Keywords: LTfLL
weblogs
social software
text mining
data mining
rss
lsa
Issue Date: 7-Aug-2009
Series/Report no.: LNCS
5794
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.
Description: Kalz, M., Beekman, N., Karsten, A., Oudshoorn, D., Van Rosmalen, P., Van Bruggen, J., & Koper, R. (2009). SWeMoF: A semantic framework to discover patterns in learning networks. In U. Cress, V. Dimitrova & M. Specht (Eds.), Learning in the Synergy of Multiple Disciplines. Proceedings of the Fourth European Conference on Technology-Enhanced Learning (EC-TEL 2009) (pp. 160-165). September, 29 - October, 2, 2009, Nice, France. Lecture Notes in Computer Science Vol. 5794. Berlin: Springer-Verlag.
URI: http://hdl.handle.net/1820/2003
ISBN: 978-3-642-04635-3
Appears in Collections:1. TENC: Publications and Preprints

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