CBR Proposal for Personalizing Educational Content

  • Ana GilEmail author
  • Sara Rodríguez
  • Fernando De la Prieta
  • Juan F. De Paz
  • Beatriz Martín
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 152)


A major challenge in searching and retrieval digital content is to efficiently find the most suitable for the users. This paper proposes a new approach to filter the educational content retrieved based on Case-Based Reasoning (CBR). AIREH (Architecture for Intelligent Recovery of Educational content in Heterogeneous Environments) is a multi-agent architecture that can search and integrate heterogeneous educational content within the CBR model proposes. The recommendation model and the technologies reported in this research applied to educational content are an example of the potential for personalizing labeled educational content recovered from heterogeneous environments.


E-learning learning objects Case Base Reasoning recommender systems Multi-agent systems 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ana Gil
    • 1
    Email author
  • Sara Rodríguez
    • 1
  • Fernando De la Prieta
    • 1
  • Juan F. De Paz
    • 1
  • Beatriz Martín
    • 1
  1. 1.Departamento de Informática y Automática - Facultad de CienciasUniversity of SalamancaSalamancaSpain

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