Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional do FGV (FGV Repositório Digital) |
Texto Completo: | http://hdl.handle.net/10438/17458 |
Resumo: | With the objective to meet the health needs of the population, a huge amount of publications are generated each year. Scientific papers, thesis and dissertations become available digitally, but make them accessible to the user requires an understanding of the indexing process, which is usually made manually. This work proposes an experiment on the feasibility of automatically identify valid descriptors for the documents in the field of health. Are extracted n-grams of the texts and, after comparison with terms of vocabulary Health Sciences Descriptors (DeCS), are identified those who can act as descriptors for the works. We believe that this process can be applied to classification of document sets with deficiencies in their indexing and, even, in supporting the re-indexing processes, improving the precision and recall of the searches, and the possibility of establishing metrics of relevance. |
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Lima, Jefferson da CostaEscolas::EMApSilva, Moacyr Alvim Horta Barbosa daPedroso, Marcel de MoraesSouza, Renato Rocha2016-11-08T17:24:34Z2016-11-08T17:24:34Z2016-09-09LIMA, Jefferson da Costa. Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia. Dissertação (Mestrado em Matemática Aplicada) - Escola de Matemática Aplicada, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2016.http://hdl.handle.net/10438/17458With the objective to meet the health needs of the population, a huge amount of publications are generated each year. Scientific papers, thesis and dissertations become available digitally, but make them accessible to the user requires an understanding of the indexing process, which is usually made manually. This work proposes an experiment on the feasibility of automatically identify valid descriptors for the documents in the field of health. Are extracted n-grams of the texts and, after comparison with terms of vocabulary Health Sciences Descriptors (DeCS), are identified those who can act as descriptors for the works. We believe that this process can be applied to classification of document sets with deficiencies in their indexing and, even, in supporting the re-indexing processes, improving the precision and recall of the searches, and the possibility of establishing metrics of relevance.Com o objetivo de atender às demandas de saúde da população, uma quantidade enorme de publicações são geradas a cada ano. Artigos científicos, teses e dissertações tornam-se digitalmente disponíveis, mas torná-los acessíveis aos usuário exige a compreensão do processo de indexação, que em geral é feito manualmente. O presente trabalho propõe um experimento sobre a viabilidade de identificar automaticamente descritores válidos para documentos do campo da saúde. São extraídos n-grams dos textos e, após comparação com termos do vocabulário Descritores em Ciências da Saúde (DeCS), são identificados aqueles que podem atuar como descritores para as obras. Acreditamos que este processo pode ser aplicado na classificação de conjuntos de documentos com deficiências na indexação e, até mesmo, no apoio a processos de reindexação, melhorando a precisão e a revocação das buscas, além da possibilidade de estabelecer métricas de relevância.porProcessamento de linguagem naturalMineração de textosDescritores em ciências da saúdeMatemáticaProcessamento da linguagem natural (Computação)Mineração de dados (Computação)Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologiainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVinfo:eu-repo/semantics/openAccessTEXTJeffersonLima-Dissertação.pdf.txtJeffersonLima-Dissertação.pdf.txtExtracted 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dc.title.por.fl_str_mv |
Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia |
title |
Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia |
spellingShingle |
Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia Lima, Jefferson da Costa Processamento de linguagem natural Mineração de textos Descritores em ciências da saúde Matemática Processamento da linguagem natural (Computação) Mineração de dados (Computação) |
title_short |
Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia |
title_full |
Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia |
title_fullStr |
Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia |
title_full_unstemmed |
Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia |
title_sort |
Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia |
author |
Lima, Jefferson da Costa |
author_facet |
Lima, Jefferson da Costa |
author_role |
author |
dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EMAp |
dc.contributor.member.none.fl_str_mv |
Silva, Moacyr Alvim Horta Barbosa da Pedroso, Marcel de Moraes |
dc.contributor.author.fl_str_mv |
Lima, Jefferson da Costa |
dc.contributor.advisor1.fl_str_mv |
Souza, Renato Rocha |
contributor_str_mv |
Souza, Renato Rocha |
dc.subject.por.fl_str_mv |
Processamento de linguagem natural Mineração de textos Descritores em ciências da saúde |
topic |
Processamento de linguagem natural Mineração de textos Descritores em ciências da saúde Matemática Processamento da linguagem natural (Computação) Mineração de dados (Computação) |
dc.subject.area.por.fl_str_mv |
Matemática |
dc.subject.bibliodata.por.fl_str_mv |
Processamento da linguagem natural (Computação) Mineração de dados (Computação) |
description |
With the objective to meet the health needs of the population, a huge amount of publications are generated each year. Scientific papers, thesis and dissertations become available digitally, but make them accessible to the user requires an understanding of the indexing process, which is usually made manually. This work proposes an experiment on the feasibility of automatically identify valid descriptors for the documents in the field of health. Are extracted n-grams of the texts and, after comparison with terms of vocabulary Health Sciences Descriptors (DeCS), are identified those who can act as descriptors for the works. We believe that this process can be applied to classification of document sets with deficiencies in their indexing and, even, in supporting the re-indexing processes, improving the precision and recall of the searches, and the possibility of establishing metrics of relevance. |
publishDate |
2016 |
dc.date.accessioned.fl_str_mv |
2016-11-08T17:24:34Z |
dc.date.available.fl_str_mv |
2016-11-08T17:24:34Z |
dc.date.issued.fl_str_mv |
2016-09-09 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
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masterThesis |
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publishedVersion |
dc.identifier.citation.fl_str_mv |
LIMA, Jefferson da Costa. Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia. Dissertação (Mestrado em Matemática Aplicada) - Escola de Matemática Aplicada, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2016. |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10438/17458 |
identifier_str_mv |
LIMA, Jefferson da Costa. Análise lexicográfica da produção acadêmica da Fiocruz: uma proposta de metodologia. Dissertação (Mestrado em Matemática Aplicada) - Escola de Matemática Aplicada, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2016. |
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http://hdl.handle.net/10438/17458 |
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por |
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openAccess |
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