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Abstract
In this article, we describe a Smart Space for Learning™ (SS4L) framework and infrastructure that enables personalized access to distributed heterogeneous knowledge repositories. Helping a learner to choose an appropriate learning resource or activity is a key problem which we address in this framework, enabling personalized access to federated learning repositories with a vast number of learning offers. Our infrastructure includes personalization strategies both at the query and the query results level. Query rewriting is based on learning and language preferences; rule-based and ranking-based personalization improves these results further. Rule-based reasoning techniques are supported by formal ontologies we have developed based on standard information models for learning domains; ranking-based recommendations are supported through ensuring minimal sets of predicates appearing in query results. Our evaluation studies show that the implemented solution enables learners to find relevant learning resources in a distributed environment and through goal-based personalization improves relevancy of results.
Original language | English |
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Journal | ACM Transactions on Internet Technology |
Volume | 8 |
Issue number | 2 |
Pages (from-to) | 1-21 |
Number of pages | 21 |
ISSN | 1533-5399 |
DOIs | |
Publication status | Published - 2008 |
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KIWI: Knowledge in a Wiki
Dolog, P., Nielsen, P. A., Munk-Madsen, A., Jahn, K. & Durao, F.
01/03/2008 → 28/02/2011
Project: Research