Computational models of relevance propagation in web directories

Autores
Xamena, Eduardo; Brignole, Nélida Beatriz; Maguitman, Ana Gabriela
Año de publicación
2011
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Web Directories consist of large collections of links to websites, arranged by topic in different categories. The structure of Web Directories is typically not flat, since there are hierarchical and non-hierarchical relationships among topics. As a consequence, websites classified 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 directories. This paper proposes a family of models of relevance propagation in Web Directories. An efficient 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. It is found that some general difficulties rule out the possibility of defining flawless models of relevance propagation that only take into account structural features of Web Directories.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Computational Models
Web Directories
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:10915/125240

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spelling Computational models of relevance propagation in web directoriesXamena, EduardoBrignole, Nélida BeatrizMaguitman, Ana GabrielaCiencias InformáticasComputational ModelsWeb DirectoriesWeb Directories consist of large collections of links to websites, arranged by topic in different categories. The structure of Web Directories is typically not flat, since there are hierarchical and non-hierarchical relationships among topics. As a consequence, websites classified 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 directories. This paper proposes a family of models of relevance propagation in Web Directories. An efficient 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. It is found that some general difficulties rule out the possibility of defining flawless models of relevance propagation that only take into account structural features of Web Directories.Sociedad Argentina de Informática e Investigación Operativa2011-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf60-71http://sedici.unlp.edu.ar/handle/10915/125240enginfo:eu-repo/semantics/altIdentifier/issn/1850-2784info: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:UNLP2025-09-29T11:30:08Zoai:sedici.unlp.edu.ar:10915/125240Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:30:09.193SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Computational models of relevance propagation in web directories
title Computational models of relevance propagation in web directories
spellingShingle Computational models of relevance propagation in web directories
Xamena, Eduardo
Ciencias Informáticas
Computational Models
Web Directories
title_short Computational models of relevance propagation in web directories
title_full Computational models of relevance propagation in web directories
title_fullStr Computational models of relevance propagation in web directories
title_full_unstemmed Computational models of relevance propagation in web directories
title_sort Computational models of relevance propagation in web directories
dc.creator.none.fl_str_mv Xamena, Eduardo
Brignole, Nélida Beatriz
Maguitman, Ana Gabriela
author Xamena, Eduardo
author_facet Xamena, Eduardo
Brignole, Nélida Beatriz
Maguitman, Ana Gabriela
author_role author
author2 Brignole, Nélida Beatriz
Maguitman, Ana Gabriela
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Computational Models
Web Directories
topic Ciencias Informáticas
Computational Models
Web Directories
dc.description.none.fl_txt_mv Web Directories consist of large collections of links to websites, arranged by topic in different categories. The structure of Web Directories is typically not flat, since there are hierarchical and non-hierarchical relationships among topics. As a consequence, websites classified 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 directories. This paper proposes a family of models of relevance propagation in Web Directories. An efficient 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. It is found that some general difficulties rule out the possibility of defining flawless models of relevance propagation that only take into account structural features of Web Directories.
Sociedad Argentina de Informática e Investigación Operativa
description Web Directories consist of large collections of links to websites, arranged by topic in different categories. The structure of Web Directories is typically not flat, since there are hierarchical and non-hierarchical relationships among topics. As a consequence, websites classified 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 directories. This paper proposes a family of models of relevance propagation in Web Directories. An efficient 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. It is found that some general difficulties rule out the possibility of defining flawless models of relevance propagation that only take into account structural features of Web Directories.
publishDate 2011
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