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CBR Proposal for Personalizing Educational Content: Profile on PlumX
Título : CBR Proposal for Personalizing Educational Content
Autor(es) : Gil González, Ana Belén
Prieta Pintado, Fernando de la
Paz Santana, Juan Francisco de
Martín, Beatriz
Rodríguez González, Sara
Palabras clave : Computer Science
Fecha de publicación : 2012
Editor : Springer Science + Business Media
Citación : Advances in Intelligent and Soft Computing International Workshop on Evidence-Based Technology Enhanced Learning. pp. 115-123.
Resumen : 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. 
URI : http://dx.doi.org/10.1007/978-3-642-28801-2_14
http://hdl.handle.net/10366/134841
ISSN : http://id.crossref.org/isbn/978-3-642-28800-5(Print)/ http://id.crossref.org/isbn/978-3-642-28801-2(Online)
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