Discovering Wikipedia Conventions Using DBpedia Properties

Autores
Torres, Diego; Skaf-Molli, Hala; Molli, Pascal; Díaz, Alicia
Año de publicación
2016
Idioma
español castellano
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Wikipedia is a public and universal encyclopedia where contributors edit articles collaboratively. Wikipedia infoboxes and categories have been used by semantic technologies to create DBpedia, a knowledge base that semantically describes Wikipedia content and makes it publicly available on the Web. Semantic descriptions of DBpedia can be exploited not only for data retrieval, but also for identifying missing navigational paths in Wikipedia. Existing approaches have demonstrated that missing navigational paths are useful for the Wikipedia community, but their injection has to respect the Wikipedia convention. In this paper, we present a collaborative recommender system approach named BlueFinder, to enhance Wikipedia content with DBpedia properties. BlueFinder implements a supervised learning algorithm to predict the Wikipedia conventions used to represent similar connected pairs of articles; these predictions are used to recommend the best conventions to connect disconnected articles. We report on an exhaustive evaluation that shows three remarkable elements: 1 The evidence of a relevant information gap between DBpedia and Wikipedia; 2 Behavior and accuracy of the BlueFinder algorithm; and 3 Differences in Wikipedia conventions according to the specificity of the involved articles. BlueFinder assists Wikipedia contributors to add missing relations between articles, and consequently, it improves Wikipedia content.
Trabajo publicado en Lecture Notes in Computer Science book series (LNCS, vol. 9507).
Laboratorio de Investigación y Formación en Informática Avanzada
Materia
Ciencias Informáticas
Semantic web
Social web
DBpedia
Wikipedia
Collaborative Recommender Systems
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/127044
Acceder
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spelling Discovering Wikipedia Conventions Using DBpedia PropertiesTorres, DiegoSkaf-Molli, HalaMolli, PascalDíaz, AliciaCiencias InformáticasSemantic webSocial webDBpediaWikipediaCollaborative Recommender SystemsWikipedia is a public and universal encyclopedia where contributors edit articles collaboratively. Wikipedia infoboxes and categories have been used by semantic technologies to create DBpedia, a knowledge base that semantically describes Wikipedia content and makes it publicly available on the Web. Semantic descriptions of DBpedia can be exploited not only for data retrieval, but also for identifying missing navigational paths in Wikipedia. Existing approaches have demonstrated that missing navigational paths are useful for the Wikipedia community, but their injection has to respect the Wikipedia convention. In this paper, we present a collaborative recommender system approach named BlueFinder, to enhance Wikipedia content with DBpedia properties. BlueFinder implements a supervised learning algorithm to predict the Wikipedia conventions used to represent similar connected pairs of articles; these predictions are used to recommend the best conventions to connect disconnected articles. We report on an exhaustive evaluation that shows three remarkable elements: 1 The evidence of a relevant information gap between DBpedia and Wikipedia; 2 Behavior and accuracy of the BlueFinder algorithm; and 3 Differences in Wikipedia conventions according to the specificity of the involved articles. BlueFinder assists Wikipedia contributors to add missing relations between articles, and consequently, it improves Wikipedia content.Trabajo publicado en <i>Lecture Notes in Computer Science</i> book series (LNCS, vol. 9507).Laboratorio de Investigación y Formación en Informática Avanzada2016info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf115-144http://sedici.unlp.edu.ar/handle/10915/127044spainfo:eu-repo/semantics/altIdentifier/isbn/978-3-319-32667-2info:eu-repo/semantics/altIdentifier/issn/0302-9743info:eu-repo/semantics/altIdentifier/issn/1611-3349info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-319-32667-2_6info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T11:02:48Zoai:sedici.unlp.edu.ar:10915/127044Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 11:02:48.685SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Discovering Wikipedia Conventions Using DBpedia Properties
title Discovering Wikipedia Conventions Using DBpedia Properties
spellingShingle Discovering Wikipedia Conventions Using DBpedia Properties
Torres, Diego
Ciencias Informáticas
Semantic web
Social web
DBpedia
Wikipedia
Collaborative Recommender Systems
title_short Discovering Wikipedia Conventions Using DBpedia Properties
title_full Discovering Wikipedia Conventions Using DBpedia Properties
title_fullStr Discovering Wikipedia Conventions Using DBpedia Properties
title_full_unstemmed Discovering Wikipedia Conventions Using DBpedia Properties
title_sort Discovering Wikipedia Conventions Using DBpedia Properties
dc.creator.none.fl_str_mv Torres, Diego
Skaf-Molli, Hala
Molli, Pascal
Díaz, Alicia
author Torres, Diego
author_facet Torres, Diego
Skaf-Molli, Hala
Molli, Pascal
Díaz, Alicia
author_role author
author2 Skaf-Molli, Hala
Molli, Pascal
Díaz, Alicia
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Semantic web
Social web
DBpedia
Wikipedia
Collaborative Recommender Systems
topic Ciencias Informáticas
Semantic web
Social web
DBpedia
Wikipedia
Collaborative Recommender Systems
dc.description.none.fl_txt_mv Wikipedia is a public and universal encyclopedia where contributors edit articles collaboratively. Wikipedia infoboxes and categories have been used by semantic technologies to create DBpedia, a knowledge base that semantically describes Wikipedia content and makes it publicly available on the Web. Semantic descriptions of DBpedia can be exploited not only for data retrieval, but also for identifying missing navigational paths in Wikipedia. Existing approaches have demonstrated that missing navigational paths are useful for the Wikipedia community, but their injection has to respect the Wikipedia convention. In this paper, we present a collaborative recommender system approach named BlueFinder, to enhance Wikipedia content with DBpedia properties. BlueFinder implements a supervised learning algorithm to predict the Wikipedia conventions used to represent similar connected pairs of articles; these predictions are used to recommend the best conventions to connect disconnected articles. We report on an exhaustive evaluation that shows three remarkable elements: 1 The evidence of a relevant information gap between DBpedia and Wikipedia; 2 Behavior and accuracy of the BlueFinder algorithm; and 3 Differences in Wikipedia conventions according to the specificity of the involved articles. BlueFinder assists Wikipedia contributors to add missing relations between articles, and consequently, it improves Wikipedia content.
Trabajo publicado en <i>Lecture Notes in Computer Science</i> book series (LNCS, vol. 9507).
Laboratorio de Investigación y Formación en Informática Avanzada
description Wikipedia is a public and universal encyclopedia where contributors edit articles collaboratively. Wikipedia infoboxes and categories have been used by semantic technologies to create DBpedia, a knowledge base that semantically describes Wikipedia content and makes it publicly available on the Web. Semantic descriptions of DBpedia can be exploited not only for data retrieval, but also for identifying missing navigational paths in Wikipedia. Existing approaches have demonstrated that missing navigational paths are useful for the Wikipedia community, but their injection has to respect the Wikipedia convention. In this paper, we present a collaborative recommender system approach named BlueFinder, to enhance Wikipedia content with DBpedia properties. BlueFinder implements a supervised learning algorithm to predict the Wikipedia conventions used to represent similar connected pairs of articles; these predictions are used to recommend the best conventions to connect disconnected articles. We report on an exhaustive evaluation that shows three remarkable elements: 1 The evidence of a relevant information gap between DBpedia and Wikipedia; 2 Behavior and accuracy of the BlueFinder algorithm; and 3 Differences in Wikipedia conventions according to the specificity of the involved articles. BlueFinder assists Wikipedia contributors to add missing relations between articles, and consequently, it improves Wikipedia content.
publishDate 2016
dc.date.none.fl_str_mv 2016
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