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1
Contrastive study between converse constructions in Brazilian and European Portuguese ; Estudo contrastivo sobre as construções conversas em PB e PE
In: Léxico e suas interfaces. Descrição, reflexão e ensino ; https://hal.archives-ouvertes.fr/hal-01403345 ; Odair Luiz Nadin; Anise de Abreu Gonçalves D'Orange Ferreira; Cristina Martins Fargetti. Léxico e suas interfaces. Descrição, reflexão e ensino, 29, Cultura Acadêmica, pp.199-218, 2016, Série Trilhas Linguísticas, 978-85-7983-806-4 ; http://www.fclar.unesp.br/Home/Instituicao/Administracao/DivisaoTecnicaAcademica/ApoioaoEnsino/LaboratorioEditorial/serie-trilhas-linguisticas-n29---e-book.pdf (2016)
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2
Automated anonymization of text documents
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3
O uso de provérbios no ensino de português
Reis, Sónia; Baptista, Jorge. - : Soares, & Lauhakangas, Outi, 2016
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4
Automatic generation of exercises on passive transformation in portuguese
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5
Portuguese proverbs: types and variants
Reis, Sónia; Baptista, Jorge. - : Editions Tradulex, 2016
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6
Lexicon-grammar of Russian verbal idioms
Fukova, Tetyana. - 2016
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7
Assisting European Portuguese teaching: linguistic features extraction and automatic readability classifier
Curto, Pedro; Baptista, Jorge; Mamede, Nuno. - : Inst Syst & Technologies Informat, Control & Commun; Int Soc Engn EducInst Syst & Technologies Informat, Control & Commun; Int Soc Engn Educ, 2016
Abstract: This paper describes two automatic systems: a linguistic features extractor and a text readability classifier for European Portuguese texts. Its main goal is to assist the selection of adequate reading materials to support Portuguese teaching, especially as a second language. To the feature extraction from texts, the system uses several Natural Language Processing (NLP) tools. Currently, 52 features are extracted: parts-of-speech (POS), syllables, words, chunks and phrases, averages and frequencies, among others. A classifier was created using these features and a corpus, previously annotated readability level, adopting the five-levels language classification official standard for Portuguese as Second Language. In a five-levels (from A1 to C1) scenario, the best-performing learning algorithm (LogitBoost) achieved an accuracy of 75.11% with a root mean square error (RMSE) of 0.269. In a three-levels (A, B and C) scenario, the best-performing learning algorithm (C4.5 grafted) achieved 81.44% accuracy, with a RMSE of 0.346.
URL: http://hdl.handle.net/10400.1/9766
https://doi.org/10.1007/978-3-319-29585-5_5
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8
Let's play with proverbs? NLP tools and resources for iCALL applications around proverbs for PFL
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9
Syntax Deep Explorer
Baptista, Jorge; Mamede, Nuno; Correia, José. - : SPRINGER INT PUBLISHING AG, 2016
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