Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources

Social networking potentially offers improved distance learning environments by enabling the exchange of resources between learners. The existence of properly classified content results in an enhanced distance learning experience in which appropriate materials can be retrieved efficiently; however,...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Andrés García-Floriano, Ángel Ferreira-Santiago, Cornelio Yáñez-Márquez, Oscar Camacho-Nieto, Mario Aldape-Pérez, Yenny Villuendas-Rey
Formato:	article
Lenguaje:	EN
Publicado:	Athabasca University Press 2017
Materias:	social networking distance learning social web content metadata generation intelligent classification Special aspects of education LC8-6691
Acceso en línea:	https://doaj.org/article/07eddb2b0a73493a900d0c53b6a1bb09
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:07eddb2b0a73493a900d0c53b6a1bb09
record_format	dspace
spelling	oai:doaj.org-article:07eddb2b0a73493a900d0c53b6a1bb092021-12-02T17:00:16ZSocial Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources10.19173/irrodl.v18i1.26461492-3831https://doaj.org/article/07eddb2b0a73493a900d0c53b6a1bb092017-02-01T00:00:00Zhttp://www.irrodl.org/index.php/irrodl/article/view/2646https://doaj.org/toc/1492-3831Social networking potentially offers improved distance learning environments by enabling the exchange of resources between learners. The existence of properly classified content results in an enhanced distance learning experience in which appropriate materials can be retrieved efficiently; however, for this to happen, metadata needs to be present. As manual metadata generation is time-costly and often eschewed by the authors of the social web resources, automatic generation is a fertile area for research as several kinds of metadata, such as author or topic, can be generated or extracted from the contents of a document. In this paper we propose a novel metadata generation system aimed at automatically tagging distance learning resources. This system is based on a recently-created intelligent pattern classifier; specifically, it trains on a corpus of example documents and then predicts the topic of a new document based on its text content. Metadata is generated in order to achieve a better integration of the web resources with the social networks. Experimental results for a two-class problem are promising and encourage research geared towards applying this method to multiple topics. Andrés García-FlorianoÁngel Ferreira-SantiagoCornelio Yáñez-MárquezOscar Camacho-NietoMario Aldape-PérezYenny Villuendas-ReyAthabasca University Pressarticlesocial networkingdistance learningsocial web contentmetadata generationintelligent classificationSpecial aspects of educationLC8-6691ENInternational Review of Research in Open and Distributed Learning, Vol 18, Iss 1 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	social networking distance learning social web content metadata generation intelligent classification Special aspects of education LC8-6691
spellingShingle	social networking distance learning social web content metadata generation intelligent classification Special aspects of education LC8-6691 Andrés García-Floriano Ángel Ferreira-Santiago Cornelio Yáñez-Márquez Oscar Camacho-Nieto Mario Aldape-Pérez Yenny Villuendas-Rey Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources
description	Social networking potentially offers improved distance learning environments by enabling the exchange of resources between learners. The existence of properly classified content results in an enhanced distance learning experience in which appropriate materials can be retrieved efficiently; however, for this to happen, metadata needs to be present. As manual metadata generation is time-costly and often eschewed by the authors of the social web resources, automatic generation is a fertile area for research as several kinds of metadata, such as author or topic, can be generated or extracted from the contents of a document. In this paper we propose a novel metadata generation system aimed at automatically tagging distance learning resources. This system is based on a recently-created intelligent pattern classifier; specifically, it trains on a corpus of example documents and then predicts the topic of a new document based on its text content. Metadata is generated in order to achieve a better integration of the web resources with the social networks. Experimental results for a two-class problem are promising and encourage research geared towards applying this method to multiple topics.
format	article
author	Andrés García-Floriano Ángel Ferreira-Santiago Cornelio Yáñez-Márquez Oscar Camacho-Nieto Mario Aldape-Pérez Yenny Villuendas-Rey
author_facet	Andrés García-Floriano Ángel Ferreira-Santiago Cornelio Yáñez-Márquez Oscar Camacho-Nieto Mario Aldape-Pérez Yenny Villuendas-Rey
author_sort	Andrés García-Floriano
title	Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources
title_short	Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources
title_full	Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources
title_fullStr	Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources
title_full_unstemmed	Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources
title_sort	social web content enhancement in a distance learning environment: intelligent metadata generation for resources
publisher	Athabasca University Press
publishDate	2017
url	https://doaj.org/article/07eddb2b0a73493a900d0c53b6a1bb09
work_keys_str_mv	AT andresgarciafloriano socialwebcontentenhancementinadistancelearningenvironmentintelligentmetadatagenerationforresources AT angelferreirasantiago socialwebcontentenhancementinadistancelearningenvironmentintelligentmetadatagenerationforresources AT cornelioyanezmarquez socialwebcontentenhancementinadistancelearningenvironmentintelligentmetadatagenerationforresources AT oscarcamachonieto socialwebcontentenhancementinadistancelearningenvironmentintelligentmetadatagenerationforresources AT marioaldapeperez socialwebcontentenhancementinadistancelearningenvironmentintelligentmetadatagenerationforresources AT yennyvilluendasrey socialwebcontentenhancementinadistancelearningenvironmentintelligentmetadatagenerationforresources
_version_	1718382251209654272

Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources

Ejemplares similares