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Título
CBR Proposal for Personalizing Educational Content
Autor(es)
Materia
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
ISSN
http://id.crossref.org/isbn/978-3-642-28800-5(Print)/ http://id.crossref.org/isbn/978-3-642-28801-2(Online)
Colecciones
- BISITE. Congresos [288]