Personalizing access to learning networks

  • Authors:
  • Peter Dolog;Bernd Simon;Wolfgang Nejdl;Tomaž Klobučar

  • Affiliations:
  • Aalborg University, Aalborg, Denmark;Vienna University of Economics and Business Administration, Vienna, Austria;University of Hannover, Hannover, Germany;Jozef Stefan Institute, Ljubljana, Slovenia

  • Venue:
  • ACM Transactions on Internet Technology (TOIT)
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

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.