&lt;b&gt;Extração automática de termos compostos para construção de ontologias: um experimento na área da saúde&lt;/b&gt;

Lopes, Lucelene; Vieira, Renata; Finatto, Maria José Bocorny; Martins, Daniel Ganzarolli; Zanette, Adriano; Ribeiro, Luiz Carlos

doi:10.3395/reciis.v3i1.244pt

Cited by 3 publications

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“…Up to date, it was possible to find only two papers that used linguistic knowledge of the semantic level, [71] and a dissertation [53] published in [14]. However, we found no contribution that used knowledge at the pragmatic level.…”

Section: Discussion About the State Of The Art In Term Extraction Forcontrasting

confidence: 41%

“…There is also the work of Lopes et al [71] that used the OntoLP tool [53] to compare three ways of term extraction (bigrams and trigrams) based on the linguistic approach. The first way considered only n-grams, the second one used pre-established morphosyntactic patterns, while the third one only considered the noun phrases.…”

Section: Research Developed For Brazilian Portuguese Term Extractionmentioning

confidence: 99%

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A survey of automatic term extraction for Brazilian Portuguese

Conrado

Felippo

Pardo³

et al. 2014

J Braz Comput Soc

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Background: Term extraction is highly relevant as it is the basis for several tasks, such as the building of dictionaries, taxonomies, and ontologies, as well as the translation and organization of text data. Methods and Results:In this paper, we present a survey of the state of the art in automatic term extraction (ATE) for the Brazilian Portuguese language. In this sense, the main contributions and projects related to such task have been classified according to the knowledge they use: statistical, linguistic, and hybrid (statistical and linguistic). We also present a study/review of the corpora used in the term extraction in Brazilian Portuguese, as well as a geographic mapping of Brazil regarding such contributions, projects, and corpora, considering their origins. Conclusions: In spite of the importance of the ATE, there are still several gaps to be filled, for instance, the lack of consensus regarding the formal definition of meaning of 'term'. Such gaps are larger for the Brazilian Portuguese when compared to other languages, such as English, Spanish, and French. Examples of gaps for Brazilian Portuguese include the lack of a baseline ATE system, as well as the use of more sophisticated linguistic information, such as the WordNet and Wikipedia knowledge bases. Nevertheless, there is an increase in the number of contributions related to ATE and an interesting tendency to use contrasting corpora and domain stoplists, even though most contributions only use frequency, noun phrases, and morphosyntactic patterns.

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Section: Discussion About the State Of The Art In Term Extraction Forcontrasting

confidence: 41%

Section: Research Developed For Brazilian Portuguese Term Extractionmentioning

confidence: 99%

A survey of automatic term extraction for Brazilian Portuguese

Conrado

Felippo

Pardo³

et al. 2014

J Braz Comput Soc

View full text Add to dashboard Cite

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“…Breno Fabrício Terra Azevedo, Hélvia Pereira Pinto Bastos Mineração de dados textuais educacionais: experiências e perspectivas para a análise de postagens em fóruns de discussão O processamento computacional de documentos escritos costuma se apoiar nas seguintes abordagens (LOPES et al, 2009;MORAIS, AMBRÓSIO, 2007):…”

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Mineração de Dados Textuais Educacionais: Experiências e Perspectivas para a Análise de Postagens em Fóruns de Discussão

Azevedo¹,

Bastos²

Tecnologias Digitais Na Educação: Pesquisas E Práticas Pedagógicas

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Identification of Multiword Expressions in Technical Domains: Investigating Statistical and Alignment-Based Approaches

Villavicencio

Caseli

Machado

2009

2009 Seventh Brazilian Symposium in Information and Human Language Technology

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Multiword Expressions (MWEs) are one of the stumbling blocks for more precise Natural Language Processing (NLP) systems. The lack of coverage of MWEs in resources can impact negatively on the performance of tasks and applications, and can lead to loss of information or communication errors; especially in technical domains where MWE are frequent. This paper investigates some approaches to the identification of MWEs in technical corpora based on: association measures, part-of-speech and lexical alignment information. We examine the influence of some factors on their performance such as sources of information for identification and evaluation. While the association measures emphasize recall, the alignment method focuses on precision.

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<b>Extração automática de termos compostos para construção de ontologias: um experimento na área da saúde</b>

Abstract: Este Apêndice apresenta os 70 primeiros termos identificados em cada método (tri-gramas) com exclusão de termos. Os termos extraídos que constam na referência estão destacados.

Cited by 3 publications

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A survey of automatic term extraction for Brazilian Portuguese

A survey of automatic term extraction for Brazilian Portuguese

Mineração de Dados Textuais Educacionais: Experiências e Perspectivas para a Análise de Postagens em Fóruns de Discussão

Identification of Multiword Expressions in Technical Domains: Investigating Statistical and Alignment-Based Approaches

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