Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/11562
Title: | Just in time and relevant knowledge thanks to recommender systems and sementic web | Authors: | Plessers, Ben Van Hyfte, Dirk SCHREURS, Jeanne |
Issue Date: | 2010 | Publisher: | International Association on Online Engineering | Source: | Auer, Michael & Schreurs, Jeanne (Ed.) Academic and corporate e-learning in a global context. p. 583-589. | Abstract: | Recommender systems are software sytems that supply users with information in order to help them make decisions, without users have to search for it themselves. A recommender system in an e-learning context is a software agent that tries to "intelligently" recommend actions to a learner based on the actions of previous learners. These recommendations could be on-line activities such as doing an exercise, reading posted messages on a conferencing sytem, or running an on-line simulation, or could be simply a web resource. This paper will make a description for a recommender system that will make use of the Semantic Web and Linked Data. The proposed recommender system will have a Text Mining Module and a Recommender Moduleto make relevant, just in time suggestions to the user. | Document URI: | http://hdl.handle.net/1942/11562 | ISBN: | 978-3-89958-541-4 | Category: | C1 | Type: | Proceedings Paper |
Appears in Collections: | Research publications |
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.