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Ranking Keyphrases from Semantic and Syntactic Features of Textual Terms.

, , and . BRACIS, page 134-139. IEEE Computer Society, (2015)

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Learning keyphrases from corpora and knowledge models., , and . Nat. Lang. Eng., 26 (3): 293-318 (2020)LegalBert-pt: A Pretrained Language Model for the Brazilian Portuguese Legal Domain., , , , and . BRACIS (3), volume 14197 of Lecture Notes in Computer Science, page 268-282. Springer, (2023)Uma Abordagem Baseada em Agentes para o Teste Caixa Preta de Agentes Racionais: Um Estudo de Caso com Agentes Reativos., , and . SBQS, page 61-75. SBC, (2014)Using Non-textual Terms for Boosting Document Keyphrase Assignment., , and . WI-IAT (1), page 260-267. IEEE Computer Society, (2015)Towards Keyphrase Assignment for Texts in Portuguese Language., , and . PROPOR, volume 9727 of Lecture Notes in Computer Science, page 165-176. Springer, (2016)Using Topic Modeling in Classification of Brazilian Lawsuits., , , , and . PROPOR, volume 13208 of Lecture Notes in Computer Science, page 233-242. Springer, (2022)CDJUR-BR - A Golden Collection of Legal Document from Brazilian Justice with Fine-Grained Named Entities., , , , , , , and . CoRR, (2023)Ranking Keyphrases from Semantic and Syntactic Features of Textual Terms., , and . BRACIS, page 134-139. IEEE Computer Society, (2015)