Personalisation Services for Self e-Learning Networks

Kevin Keenoy 1 Alexandra Poulovassilis 1 Vassilis Christophides 2 Philippe Rigaux 3 George Papamarkos 1 Aimilia Magkanaraki 2 Miltos Stratakis 2 Nicolas Spyratos 3 Peter Wood 1
1 School of Computer Science and Information Systems
2 ICS-FORTH - Institute of Computer Science
3 LRI - Laboratoire de Recherche en Informatique
Abstract : This paper describes the personalisation services designed for self e-learning networks in the SeLeNe project. A self e-learning network consists of web-based learning objects that have been made available to the network by its users, along with metadata descriptions of these learning objects and of the network's users. The proposed personalisation facilities include: querying learning object descriptions to return results tailored towards users' individual goals and preferences; the ability to define views over the learning object metadata; facilities for defining new composite learning objects; and facilities for subscribing to personalised event and change notification services. We show the feasibility of automatically deriving descriptions for composite learning objects and of realising the personalisation facilities using a service-based architecture, employing a combination of existing and new Semantic Web technologies including RDF/S, RQL, RVL, and ECA rules.
Keywords : personalisation peer-to-peer learning networks resource description frame (RDF)
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Kevin Keenoy, Alexandra Poulovassilis, Vassilis Christophides, Philippe Rigaux, George Papamarkos, et al.. Personalisation Services for Self e-Learning Networks. 2nd IST Workshop on Metadata Management in Grid and P2P Systems: Models, Services and Architectures (MMGPS'04), 2004, London, United Kingdom. 14 p. ⟨hal-00190421⟩

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