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Adaptive hybrid recommender system of learning objects

This paper presents the general architecture of an adaptive recommender system of learning objects, whose recommendations combine three distinct aspects: contents, collaboration and knowledge. The recommender system is implemented like a semantic web service, designed with the framework FODAS-WS, wh...

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Autor Principal: Aguilar, Jos? L.
Formato: Artículos
Lenguaje:eng
Publicado: Estados Unidos 2017
Materias:
INTELLIGENT RECOMMENDER SYSTEMS
LEARNING OBJECTS
LEARNING STYLE
CALIBRATION OF RECOMMENDERS
Acceso en línea:http://repositorio.educacionsuperior.gob.ec/handle/28000/4671
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spelling oai:localhost:28000-46712017-10-17T15:33:09Z Adaptive hybrid recommender system of learning objects Aguilar, Jos? L. INTELLIGENT RECOMMENDER SYSTEMS LEARNING OBJECTS LEARNING STYLE CALIBRATION OF RECOMMENDERS This paper presents the general architecture of an adaptive recommender system of learning objects, whose recommendations combine three distinct aspects: contents, collaboration and knowledge. The recommender system is implemented like a semantic web service, designed with the framework FODAS-WS, which allows the specification of computational systems using ontologies, using the ODA (Ontology Driven Architecture) paradigm. 2017-10-17T15:33:01Z 2017-10-17T15:33:01Z 2016 article Aguilar, Jos?; Portilla, Omar; Puerto, Eduard. (2016). Adaptive hybrid recommender system of learning objects. IEEE Latin America Conference. Estados Unidos. 978-1-5090-5105-2 http://repositorio.educacionsuperior.gob.ec/handle/28000/4671 eng DOI;10.1109/LA-CCI.2016.7885707 closedAccess http://creativecommons.org/licenses/by-nc-sa/3.0/ec/ Estados Unidos
institution SENESCYT
collection Repositorio SENESCYT
biblioteca Biblioteca Senescyt
language eng
format Artículos
topic INTELLIGENT RECOMMENDER SYSTEMS
LEARNING OBJECTS
LEARNING STYLE
CALIBRATION OF RECOMMENDERS
spellingShingle INTELLIGENT RECOMMENDER SYSTEMS
LEARNING OBJECTS
LEARNING STYLE
CALIBRATION OF RECOMMENDERS
Aguilar, Jos? L.
Adaptive hybrid recommender system of learning objects
description This paper presents the general architecture of an adaptive recommender system of learning objects, whose recommendations combine three distinct aspects: contents, collaboration and knowledge. The recommender system is implemented like a semantic web service, designed with the framework FODAS-WS, which allows the specification of computational systems using ontologies, using the ODA (Ontology Driven Architecture) paradigm.
author Aguilar, Jos? L.
author_facet Aguilar, Jos? L.
author_sort Aguilar, Jos? L.
title Adaptive hybrid recommender system of learning objects
title_short Adaptive hybrid recommender system of learning objects
title_full Adaptive hybrid recommender system of learning objects
title_fullStr Adaptive hybrid recommender system of learning objects
title_full_unstemmed Adaptive hybrid recommender system of learning objects
title_sort adaptive hybrid recommender system of learning objects
publisher Estados Unidos
publishDate 2017
url http://repositorio.educacionsuperior.gob.ec/handle/28000/4671
_version_ 1634995272554643456
score 11,871979

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