2026-08-28T07:00:27Zhttps://gredos.usal.es/oai/request

oai:gredos.usal.es:10366/1348412025-04-30T20:37:53Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134811

Gil González, Ana Belén Prieta Pintado, Fernando de la De Paz, Juan F. Martín, Beatriz Rodríguez González, Sara 2017-09-06T09:14:06Z 2017-09-06T09:14:06Z 2012 Advances in Intelligent and Soft Computing International Workshop on Evidence-Based Technology Enhanced Learning. pp. 115-123. http://id.crossref.org/isbn/978-3-642-28800-5(Print)/ http://id.crossref.org/isbn/978-3-642-28801-2(Online) http://dx.doi.org/10.1007/978-3-642-28801-2_14 http://hdl.handle.net/10366/134841 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.  en info:eu-repo/semantics/openAccess Computer Science CBR Proposal for Personalizing Educational Content info:eu-repo/semantics/conferenceObject