A study of relevance propagation in large topic ontologies

Autores
Xamena, Eduardo; Brignole, Nelida Beatriz; Maguitman, Ana Gabriela
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Topic ontologies or Web Directories consist of large collections of links to websites,arranged by topic in different categories. The structure of these ontologies is typically not at, since there are hierarchical and non-hierarchical relationships among topics. As a consequence, websites classied under certain topic may be relevant to other topics. While some of these relevance relations are explicit, most of them must be discovered by an analysis of the structure of these ontologies. This paper proposes a family of models of relevance propagation in topic ontologies. An ecient computational framework for inferring implicit relevance relations is described. The framework presented here combines the use of matrices to represent relevance relations and the application of boolean operations on these matrices to infer implicit relations. Nine different models were computed for a portion of the Open Directory Project graph consisting of more than half a million nodes and approximately 1.5 million edges of different types. The models were compared by performing both a quantitative and qualitative analysis on them. In addition, a user study was carried out to compare the most promising models. It is found that some general difficulties rule out the possibility of defining flawless models of relevance propagation that only take into account structural aspects of an ontology. However, there is a clear indication that including transitive relations induced by the non-hierarchical components of the ontology results in relevance propagation models that are superior to more basic approaches.
Fil: Xamena, Eduardo. Universidad Nacional del Sur. Departamento de Cs.e Ing.de la Computacion. Laboratorio de Inv. y Des. En Computacion Cientifica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
Fil: Brignole, Nelida Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
Fil: Maguitman, Ana Gabriela. Universidad Nacional del Sur. Departamento de Cs.e Ing.de la Computacion; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
Relevance Propagation
Topic Ontologies
Semantic Similarity
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/10430

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spelling A study of relevance propagation in large topic ontologiesXamena, EduardoBrignole, Nelida BeatrizMaguitman, Ana GabrielaRelevance PropagationTopic OntologiesSemantic Similarityhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Topic ontologies or Web Directories consist of large collections of links to websites,arranged by topic in different categories. The structure of these ontologies is typically not at, since there are hierarchical and non-hierarchical relationships among topics. As a consequence, websites classied under certain topic may be relevant to other topics. While some of these relevance relations are explicit, most of them must be discovered by an analysis of the structure of these ontologies. This paper proposes a family of models of relevance propagation in topic ontologies. An ecient computational framework for inferring implicit relevance relations is described. The framework presented here combines the use of matrices to represent relevance relations and the application of boolean operations on these matrices to infer implicit relations. Nine different models were computed for a portion of the Open Directory Project graph consisting of more than half a million nodes and approximately 1.5 million edges of different types. The models were compared by performing both a quantitative and qualitative analysis on them. In addition, a user study was carried out to compare the most promising models. It is found that some general difficulties rule out the possibility of defining flawless models of relevance propagation that only take into account structural aspects of an ontology. However, there is a clear indication that including transitive relations induced by the non-hierarchical components of the ontology results in relevance propagation models that are superior to more basic approaches.Fil: Xamena, Eduardo. Universidad Nacional del Sur. Departamento de Cs.e Ing.de la Computacion. Laboratorio de Inv. y Des. En Computacion Cientifica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); ArgentinaFil: Brignole, Nelida Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); ArgentinaFil: Maguitman, Ana Gabriela. Universidad Nacional del Sur. Departamento de Cs.e Ing.de la Computacion; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaJohn Wiley & Sons Inc2013-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/10430Xamena, Eduardo; Brignole, Nelida Beatriz; Maguitman, Ana Gabriela; A study of relevance propagation in large topic ontologies; John Wiley & Sons Inc; Journal Of The American Society For Information Science And Technology; 64; 11; 11-2013; 2238-22551532-2882enginfo:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/wol1/doi/10.1002/asi.22925/abstractinfo:eu-repo/semantics/altIdentifier/doi/10.1002/asi.22925info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:09:20Zoai:ri.conicet.gov.ar:11336/10430instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:09:20.343CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A study of relevance propagation in large topic ontologies
title A study of relevance propagation in large topic ontologies
spellingShingle A study of relevance propagation in large topic ontologies
Xamena, Eduardo
Relevance Propagation
Topic Ontologies
Semantic Similarity
title_short A study of relevance propagation in large topic ontologies
title_full A study of relevance propagation in large topic ontologies
title_fullStr A study of relevance propagation in large topic ontologies
title_full_unstemmed A study of relevance propagation in large topic ontologies
title_sort A study of relevance propagation in large topic ontologies
dc.creator.none.fl_str_mv Xamena, Eduardo
Brignole, Nelida Beatriz
Maguitman, Ana Gabriela
author Xamena, Eduardo
author_facet Xamena, Eduardo
Brignole, Nelida Beatriz
Maguitman, Ana Gabriela
author_role author
author2 Brignole, Nelida Beatriz
Maguitman, Ana Gabriela
author2_role author
author
dc.subject.none.fl_str_mv Relevance Propagation
Topic Ontologies
Semantic Similarity
topic Relevance Propagation
Topic Ontologies
Semantic Similarity
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Topic ontologies or Web Directories consist of large collections of links to websites,arranged by topic in different categories. The structure of these ontologies is typically not at, since there are hierarchical and non-hierarchical relationships among topics. As a consequence, websites classied under certain topic may be relevant to other topics. While some of these relevance relations are explicit, most of them must be discovered by an analysis of the structure of these ontologies. This paper proposes a family of models of relevance propagation in topic ontologies. An ecient computational framework for inferring implicit relevance relations is described. The framework presented here combines the use of matrices to represent relevance relations and the application of boolean operations on these matrices to infer implicit relations. Nine different models were computed for a portion of the Open Directory Project graph consisting of more than half a million nodes and approximately 1.5 million edges of different types. The models were compared by performing both a quantitative and qualitative analysis on them. In addition, a user study was carried out to compare the most promising models. It is found that some general difficulties rule out the possibility of defining flawless models of relevance propagation that only take into account structural aspects of an ontology. However, there is a clear indication that including transitive relations induced by the non-hierarchical components of the ontology results in relevance propagation models that are superior to more basic approaches.
Fil: Xamena, Eduardo. Universidad Nacional del Sur. Departamento de Cs.e Ing.de la Computacion. Laboratorio de Inv. y Des. En Computacion Cientifica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
Fil: Brignole, Nelida Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Planta Piloto de Ingeniería Química (i); Argentina
Fil: Maguitman, Ana Gabriela. Universidad Nacional del Sur. Departamento de Cs.e Ing.de la Computacion; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Topic ontologies or Web Directories consist of large collections of links to websites,arranged by topic in different categories. The structure of these ontologies is typically not at, since there are hierarchical and non-hierarchical relationships among topics. As a consequence, websites classied under certain topic may be relevant to other topics. While some of these relevance relations are explicit, most of them must be discovered by an analysis of the structure of these ontologies. This paper proposes a family of models of relevance propagation in topic ontologies. An ecient computational framework for inferring implicit relevance relations is described. The framework presented here combines the use of matrices to represent relevance relations and the application of boolean operations on these matrices to infer implicit relations. Nine different models were computed for a portion of the Open Directory Project graph consisting of more than half a million nodes and approximately 1.5 million edges of different types. The models were compared by performing both a quantitative and qualitative analysis on them. In addition, a user study was carried out to compare the most promising models. It is found that some general difficulties rule out the possibility of defining flawless models of relevance propagation that only take into account structural aspects of an ontology. However, there is a clear indication that including transitive relations induced by the non-hierarchical components of the ontology results in relevance propagation models that are superior to more basic approaches.
publishDate 2013
dc.date.none.fl_str_mv 2013-11
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/10430
Xamena, Eduardo; Brignole, Nelida Beatriz; Maguitman, Ana Gabriela; A study of relevance propagation in large topic ontologies; John Wiley & Sons Inc; Journal Of The American Society For Information Science And Technology; 64; 11; 11-2013; 2238-2255
1532-2882
url http://hdl.handle.net/11336/10430
identifier_str_mv Xamena, Eduardo; Brignole, Nelida Beatriz; Maguitman, Ana Gabriela; A study of relevance propagation in large topic ontologies; John Wiley & Sons Inc; Journal Of The American Society For Information Science And Technology; 64; 11; 11-2013; 2238-2255
1532-2882
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/wol1/doi/10.1002/asi.22925/abstract
info:eu-repo/semantics/altIdentifier/doi/10.1002/asi.22925
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv John Wiley & Sons Inc
publisher.none.fl_str_mv John Wiley & Sons Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
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instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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