Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations

Autores
Alvez, Carlos; Vecchietti, Aldo
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Nowadays it is common to combine low-level and semantic data for image retrieval. The images are stored in databases and computer graphics algorithms are employed to get the pictures. Most of the works consider both aspects separately. In this work, using the capabilities of a commercial ORDBMS a reference architecture was implemented for recovering images, and then a performance analysis is realized using several index types to search some specific semantic data stored in the database via RDF triples. The experiments analyzed the mean recovery time of triples in tables having a hundred of thousands to millions of triples. The performance obtained using Bitmap, B-Tree and Hash Partitioned indexes are analyzed. The results obtained with the experiences performed are implemented in the reference architecture in order to speed up the pattern search.
Fil: Alvez, Carlos. Universidad Nacional de Entre Ríos; Argentina
Fil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Materia
Image Retrieval
Semantic Data
Rdf Triples
Object Relational Databases
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:11336/70259
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/70259
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Efficiency Analysis in Content Based Image Retrieval Using RDF AnnotationsAlvez, CarlosVecchietti, AldoImage RetrievalSemantic DataRdf TriplesObject Relational Databaseshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Nowadays it is common to combine low-level and semantic data for image retrieval. The images are stored in databases and computer graphics algorithms are employed to get the pictures. Most of the works consider both aspects separately. In this work, using the capabilities of a commercial ORDBMS a reference architecture was implemented for recovering images, and then a performance analysis is realized using several index types to search some specific semantic data stored in the database via RDF triples. The experiments analyzed the mean recovery time of triples in tables having a hundred of thousands to millions of triples. The performance obtained using Bitmap, B-Tree and Hash Partitioned indexes are analyzed. The results obtained with the experiences performed are implemented in the reference architecture in order to speed up the pattern search.Fil: Alvez, Carlos. Universidad Nacional de Entre Ríos; ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaSpringer Verlag2011-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/mswordapplication/pdfhttp://hdl.handle.net/11336/70259Alvez, Carlos; Vecchietti, Aldo; Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations; Springer Verlag; Lecture Notes in Computer Science; 7095; 12-2011; 285-2960302-9743CONICET DigitalCONICETenginfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:09:37Zoai:ri.conicet.gov.ar:11336/70259instacron: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:34982025-10-15 15:09:37.989CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations
title Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations
spellingShingle Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations
Alvez, Carlos
Image Retrieval
Semantic Data
Rdf Triples
Object Relational Databases
title_short Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations
title_full Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations
title_fullStr Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations
title_full_unstemmed Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations
title_sort Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations
dc.creator.none.fl_str_mv Alvez, Carlos
Vecchietti, Aldo
author Alvez, Carlos
author_facet Alvez, Carlos
Vecchietti, Aldo
author_role author
author2 Vecchietti, Aldo
author2_role author
dc.subject.none.fl_str_mv Image Retrieval
Semantic Data
Rdf Triples
Object Relational Databases
topic Image Retrieval
Semantic Data
Rdf Triples
Object Relational Databases
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Nowadays it is common to combine low-level and semantic data for image retrieval. The images are stored in databases and computer graphics algorithms are employed to get the pictures. Most of the works consider both aspects separately. In this work, using the capabilities of a commercial ORDBMS a reference architecture was implemented for recovering images, and then a performance analysis is realized using several index types to search some specific semantic data stored in the database via RDF triples. The experiments analyzed the mean recovery time of triples in tables having a hundred of thousands to millions of triples. The performance obtained using Bitmap, B-Tree and Hash Partitioned indexes are analyzed. The results obtained with the experiences performed are implemented in the reference architecture in order to speed up the pattern search.
Fil: Alvez, Carlos. Universidad Nacional de Entre Ríos; Argentina
Fil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
description Nowadays it is common to combine low-level and semantic data for image retrieval. The images are stored in databases and computer graphics algorithms are employed to get the pictures. Most of the works consider both aspects separately. In this work, using the capabilities of a commercial ORDBMS a reference architecture was implemented for recovering images, and then a performance analysis is realized using several index types to search some specific semantic data stored in the database via RDF triples. The experiments analyzed the mean recovery time of triples in tables having a hundred of thousands to millions of triples. The performance obtained using Bitmap, B-Tree and Hash Partitioned indexes are analyzed. The results obtained with the experiences performed are implemented in the reference architecture in order to speed up the pattern search.
publishDate 2011
dc.date.none.fl_str_mv 2011-12
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/11336/70259
Alvez, Carlos; Vecchietti, Aldo; Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations; Springer Verlag; Lecture Notes in Computer Science; 7095; 12-2011; 285-296
0302-9743
CONICET Digital
CONICET
url http://hdl.handle.net/11336/70259
identifier_str_mv Alvez, Carlos; Vecchietti, Aldo; Efficiency Analysis in Content Based Image Retrieval Using RDF Annotations; Springer Verlag; Lecture Notes in Computer Science; 7095; 12-2011; 285-296
0302-9743
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
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/msword
application/pdf
dc.publisher.none.fl_str_mv Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
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
_version_ 1846083244057952256
score 13.22299

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