A preliminary approach to the multilabel classification problem of Portuguese juridical documents

Detalhes bibliográficos
Autor(a) principal: Gonçalves, Teresa
Data de Publicação: 2003
Outros Autores: Quaresma, Paulo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10174/2559
Resumo: Portuguese juridical documents from Supreme Courts and the Attorney General’s Office are manually classified by juridical experts into a set of classes belonging to a taxonomy of concepts. In this paper, a preliminary approach to develop techniques to automat- ically classify these juridical documents, is proposed. As basic strategy, the integration of natural language processing techniques with machine learning ones is used. Support Vector Machines (SVM) are used as learn- ing algorithm and the obtained results are presented and compared with other approaches, such as C4.5 and Naive Bayes.
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spelling A preliminary approach to the multilabel classification problem of Portuguese juridical documentsmachine learningText classificationPortuguese juridical documents from Supreme Courts and the Attorney General’s Office are manually classified by juridical experts into a set of classes belonging to a taxonomy of concepts. In this paper, a preliminary approach to develop techniques to automat- ically classify these juridical documents, is proposed. As basic strategy, the integration of natural language processing techniques with machine learning ones is used. Support Vector Machines (SVM) are used as learn- ing algorithm and the obtained results are presented and compared with other approaches, such as C4.5 and Naive Bayes.Springer-Verlag2011-02-15T11:25:43Z2011-02-152003-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article491128 bytesapplication/pdfhttp://hdl.handle.net/10174/2559http://hdl.handle.net/10174/2559eng435-444Lecture Notes in Artificial Intelligence2902livretcg@uevora.ptpq@uevora.ptEPIA-03, 11th Portuguese Conference on Artificial IntelligenceMoura-Pires, F.Abreu, S.498Gonçalves, TeresaQuaresma, Pauloinfo: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:RCAAP2024-01-03T18:39:06Zoai:dspace.uevora.pt:10174/2559Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:58:14.281620Repositório 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 A preliminary approach to the multilabel classification problem of Portuguese juridical documents
title A preliminary approach to the multilabel classification problem of Portuguese juridical documents
spellingShingle A preliminary approach to the multilabel classification problem of Portuguese juridical documents
Gonçalves, Teresa
machine learning
Text classification
title_short A preliminary approach to the multilabel classification problem of Portuguese juridical documents
title_full A preliminary approach to the multilabel classification problem of Portuguese juridical documents
title_fullStr A preliminary approach to the multilabel classification problem of Portuguese juridical documents
title_full_unstemmed A preliminary approach to the multilabel classification problem of Portuguese juridical documents
title_sort A preliminary approach to the multilabel classification problem of Portuguese juridical documents
author Gonçalves, Teresa
author_facet Gonçalves, Teresa
Quaresma, Paulo
author_role author
author2 Quaresma, Paulo
author2_role author
dc.contributor.author.fl_str_mv Gonçalves, Teresa
Quaresma, Paulo
dc.subject.por.fl_str_mv machine learning
Text classification
topic machine learning
Text classification
description Portuguese juridical documents from Supreme Courts and the Attorney General’s Office are manually classified by juridical experts into a set of classes belonging to a taxonomy of concepts. In this paper, a preliminary approach to develop techniques to automat- ically classify these juridical documents, is proposed. As basic strategy, the integration of natural language processing techniques with machine learning ones is used. Support Vector Machines (SVM) are used as learn- ing algorithm and the obtained results are presented and compared with other approaches, such as C4.5 and Naive Bayes.
publishDate 2003
dc.date.none.fl_str_mv 2003-01-01T00:00:00Z
2011-02-15T11:25:43Z
2011-02-15
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/10174/2559
http://hdl.handle.net/10174/2559
url http://hdl.handle.net/10174/2559
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 435-444
Lecture Notes in Artificial Intelligence
2902
livre
tcg@uevora.pt
pq@uevora.pt
EPIA-03, 11th Portuguese Conference on Artificial Intelligence
Moura-Pires, F.
Abreu, S.
498
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 491128 bytes
application/pdf
dc.publisher.none.fl_str_mv Springer-Verlag
publisher.none.fl_str_mv Springer-Verlag
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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