An Argumentation Framework based on Confidence Degrees to Combine Ontology Mapping Approaches
Autor(a) principal: | |
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Data de Publicação: | 2008 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/1515 |
Resumo: | Ontology mapping has a key importance for applications such as information retrieval, database integration, and agent-communication. This paper presents an Argumentation Framework, with confidence degrees associated to the arguments, to combine ontology mapping approaches. Our agents apply individual mapping algorithms and cooperate in order to exchange their local results (arguments). Based on their preferences and confidence of the arguments, the agents compute their preferred mapping sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments. The model is evaluated using a benchmark for ontology mapping. The results are promising especially what concerns precision. |
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An Argumentation Framework based on Confidence Degrees to Combine Ontology Mapping Approachesargumentationontology mappingOntology mapping has a key importance for applications such as information retrieval, database integration, and agent-communication. This paper presents an Argumentation Framework, with confidence degrees associated to the arguments, to combine ontology mapping approaches. Our agents apply individual mapping algorithms and cooperate in order to exchange their local results (arguments). Based on their preferences and confidence of the arguments, the agents compute their preferred mapping sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments. The model is evaluated using a benchmark for ontology mapping. The results are promising especially what concerns precision.2009-04-08T15:39:13Z2009-04-082008-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article228646 bytesapplication/pdfhttp://hdl.handle.net/10174/1515http://hdl.handle.net/10174/1515eng142-150International Journal of Metadata, Semantics and Ontologies23livrecassia@di.uevora.ptpq@di.uevora.ptrenata.vieira@pucrs.br283Trojahn, CássiaQuaresma, PauloVieira, Renatainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T18:37:33Zoai:dspace.uevora.pt:10174/1515Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:57:34.335101Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
An Argumentation Framework based on Confidence Degrees to Combine Ontology Mapping Approaches |
title |
An Argumentation Framework based on Confidence Degrees to Combine Ontology Mapping Approaches |
spellingShingle |
An Argumentation Framework based on Confidence Degrees to Combine Ontology Mapping Approaches Trojahn, Cássia argumentation ontology mapping |
title_short |
An Argumentation Framework based on Confidence Degrees to Combine Ontology Mapping Approaches |
title_full |
An Argumentation Framework based on Confidence Degrees to Combine Ontology Mapping Approaches |
title_fullStr |
An Argumentation Framework based on Confidence Degrees to Combine Ontology Mapping Approaches |
title_full_unstemmed |
An Argumentation Framework based on Confidence Degrees to Combine Ontology Mapping Approaches |
title_sort |
An Argumentation Framework based on Confidence Degrees to Combine Ontology Mapping Approaches |
author |
Trojahn, Cássia |
author_facet |
Trojahn, Cássia Quaresma, Paulo Vieira, Renata |
author_role |
author |
author2 |
Quaresma, Paulo Vieira, Renata |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Trojahn, Cássia Quaresma, Paulo Vieira, Renata |
dc.subject.por.fl_str_mv |
argumentation ontology mapping |
topic |
argumentation ontology mapping |
description |
Ontology mapping has a key importance for applications such as information retrieval, database integration, and agent-communication. This paper presents an Argumentation Framework, with confidence degrees associated to the arguments, to combine ontology mapping approaches. Our agents apply individual mapping algorithms and cooperate in order to exchange their local results (arguments). Based on their preferences and confidence of the arguments, the agents compute their preferred mapping sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments. The model is evaluated using a benchmark for ontology mapping. The results are promising especially what concerns precision. |
publishDate |
2008 |
dc.date.none.fl_str_mv |
2008-01-01T00:00:00Z 2009-04-08T15:39:13Z 2009-04-08 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/1515 http://hdl.handle.net/10174/1515 |
url |
http://hdl.handle.net/10174/1515 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
142-150 International Journal of Metadata, Semantics and Ontologies 2 3 livre cassia@di.uevora.pt pq@di.uevora.pt renata.vieira@pucrs.br 283 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
228646 bytes application/pdf |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799136460279906304 |