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Multiagent System for Indexing and Retrieving Learning Objects

  • Jonas Vian
  • Ricardo Azambuja Silveira
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 89)

Abstract

This paper proposes a multiagent system application model for indexing and retrieving learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.

Keywords

Recommender Systems Learning Objects Repositories Intelligent Learning Systems 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jonas Vian
    • 1
  • Ricardo Azambuja Silveira
    • 1
  1. 1.Federal University of Santa Catarina (UFSC)FlorianópolisBrazil

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