Semantic document indexing in ontology-driven organizational memories

Autores
Ale, María Alejandra; Galli, María Rosa; Chiotti, Omar Juan Alfredo
Año de publicación
2005
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Effective document retrieval using domain knowledge and semantics is one of the major challenges in Information Retrieval. Over the last years, there has been a growing interest in ontologies as an artifact for human knowledge representation and a critical component in Knowledge Management, Semantic Web, and Business-to-Business applications. We have found that it is not easy to represent certain types of knowledge (skills or procedures) or to transform certain types of knowledge representation (knowledge contained in diagrams) into an appropriate ontological format. To overcome this problem, our proposal is to connect knowledge sources to the domain ontology associated with an Organizational Memory without forcing any transformation in the structure of the source itself. This connection will allow the semantic classification of knowledge sources so that when a user performs a query it is possible to recover the documents that have a higher probability of containing the answer.
II Workshop de Ingeniería de Software y Bases de Datos (WISBD)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Information Search and Retrieval
gestión de conocimientos
Semantics
domain ontology
organizational memory
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/23100
Acceder
id SEDICI_11263041a25c03258f2e513fe266d6c1
oai_identifier_str oai:sedici.unlp.edu.ar:10915/23100
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Semantic document indexing in ontology-driven organizational memoriesAle, María AlejandraGalli, María RosaChiotti, Omar Juan AlfredoCiencias InformáticasInformation Search and Retrievalgestión de conocimientosSemanticsdomain ontologyorganizational memoryEffective document retrieval using domain knowledge and semantics is one of the major challenges in Information Retrieval. Over the last years, there has been a growing interest in ontologies as an artifact for human knowledge representation and a critical component in Knowledge Management, Semantic Web, and Business-to-Business applications. We have found that it is not easy to represent certain types of knowledge (skills or procedures) or to transform certain types of knowledge representation (knowledge contained in diagrams) into an appropriate ontological format. To overcome this problem, our proposal is to connect knowledge sources to the domain ontology associated with an Organizational Memory without forcing any transformation in the structure of the source itself. This connection will allow the semantic classification of knowledge sources so that when a user performs a query it is possible to recover the documents that have a higher probability of containing the answer.II Workshop de Ingeniería de Software y Bases de Datos (WISBD)Red de Universidades con Carreras en Informática (RedUNCI)2005-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23100enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:55:20Zoai:sedici.unlp.edu.ar:10915/23100Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:20.962SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Semantic document indexing in ontology-driven organizational memories
title Semantic document indexing in ontology-driven organizational memories
spellingShingle Semantic document indexing in ontology-driven organizational memories
Ale, María Alejandra
Ciencias Informáticas
Information Search and Retrieval
gestión de conocimientos
Semantics
domain ontology
organizational memory
title_short Semantic document indexing in ontology-driven organizational memories
title_full Semantic document indexing in ontology-driven organizational memories
title_fullStr Semantic document indexing in ontology-driven organizational memories
title_full_unstemmed Semantic document indexing in ontology-driven organizational memories
title_sort Semantic document indexing in ontology-driven organizational memories
dc.creator.none.fl_str_mv Ale, María Alejandra
Galli, María Rosa
Chiotti, Omar Juan Alfredo
author Ale, María Alejandra
author_facet Ale, María Alejandra
Galli, María Rosa
Chiotti, Omar Juan Alfredo
author_role author
author2 Galli, María Rosa
Chiotti, Omar Juan Alfredo
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Information Search and Retrieval
gestión de conocimientos
Semantics
domain ontology
organizational memory
topic Ciencias Informáticas
Information Search and Retrieval
gestión de conocimientos
Semantics
domain ontology
organizational memory
dc.description.none.fl_txt_mv Effective document retrieval using domain knowledge and semantics is one of the major challenges in Information Retrieval. Over the last years, there has been a growing interest in ontologies as an artifact for human knowledge representation and a critical component in Knowledge Management, Semantic Web, and Business-to-Business applications. We have found that it is not easy to represent certain types of knowledge (skills or procedures) or to transform certain types of knowledge representation (knowledge contained in diagrams) into an appropriate ontological format. To overcome this problem, our proposal is to connect knowledge sources to the domain ontology associated with an Organizational Memory without forcing any transformation in the structure of the source itself. This connection will allow the semantic classification of knowledge sources so that when a user performs a query it is possible to recover the documents that have a higher probability of containing the answer.
II Workshop de Ingeniería de Software y Bases de Datos (WISBD)
Red de Universidades con Carreras en Informática (RedUNCI)
description Effective document retrieval using domain knowledge and semantics is one of the major challenges in Information Retrieval. Over the last years, there has been a growing interest in ontologies as an artifact for human knowledge representation and a critical component in Knowledge Management, Semantic Web, and Business-to-Business applications. We have found that it is not easy to represent certain types of knowledge (skills or procedures) or to transform certain types of knowledge representation (knowledge contained in diagrams) into an appropriate ontological format. To overcome this problem, our proposal is to connect knowledge sources to the domain ontology associated with an Organizational Memory without forcing any transformation in the structure of the source itself. This connection will allow the semantic classification of knowledge sources so that when a user performs a query it is possible to recover the documents that have a higher probability of containing the answer.
publishDate 2005
dc.date.none.fl_str_mv 2005-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/23100
url http://sedici.unlp.edu.ar/handle/10915/23100
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1844615811906404352
score 13.070432

Publicaciones similares