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Hybrid Multiagent System for Automatic Object Learning Classification

  • Ana Gil
  • Fernando de la Prieta
  • Vivian F. López
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6077)

Abstract

The rapid evolution within the context of e-learning is closely linked to international efforts on the standardization of learning object metadata, which provides learners in a web-based educational system with ubiquitous access to multiple distributed repositories. This article presents a hybrid agent-based architecture that enables the recovery of learning objects tagged in Learning Object Metadata (LOM) and provides individualized help with selecting learning materials to make the most suitable choice among many alternatives.

Keywords

learning object metadata learning object repositories federated search e-learning emerging e-learning technologies neural networks 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Ana Gil
    • 1
  • Fernando de la Prieta
    • 1
  • Vivian F. López
    • 1
  1. 1.Computer Science DptUniversity of SalamancaSalamancaSpain

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