Exploring the potentiality of semantic features for paraphrase detection (2020)
- Authors:
- USP affiliated authors: PARDO, THIAGO ALEXANDRE SALGUEIRO - ICMC ; ANCHIÊTA, RAFAEL TORRES - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-030-41505-1_22
- Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL; TRATAMENTO AUTOMÁTICO DE TEXTOS E DISCURSOS; APRENDIZADO COMPUTACIONAL; SEMÂNTICA
- Keywords: Paraphrase detection
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 12037, p. 228-238, 2020
- Conference titles: International Conference on Computational Processing of the Portuguese Language - PROPOR
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
ANCHIETA, Rafael Torres e PARDO, Thiago Alexandre Salgueiro. Exploring the potentiality of semantic features for paraphrase detection. . Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-41505-1_22. Acesso em: 15 fev. 2026. , 2020 -
APA
Anchieta, R. T., & Pardo, T. A. S. (2020). Exploring the potentiality of semantic features for paraphrase detection. Cham: Springer. doi:10.1007/978-3-030-41505-1_22 -
NLM
Anchieta RT, Pardo TAS. Exploring the potentiality of semantic features for paraphrase detection [Internet]. 2020 ; 12037 228-238.[citado 2026 fev. 15 ] Available from: https://doi.org/10.1007/978-3-030-41505-1_22 -
Vancouver
Anchieta RT, Pardo TAS. Exploring the potentiality of semantic features for paraphrase detection [Internet]. 2020 ; 12037 228-238.[citado 2026 fev. 15 ] Available from: https://doi.org/10.1007/978-3-030-41505-1_22 - Abstract meaning representation parsing for the brazilian portuguese language
- Semantically inspired AMR alignment for the portuguese language
- Modeling the paraphrase detection task over a heterogeneous graph network with data augmentation
- Abstract Meaning Representation Parsing for the Brazilian Portuguese Language
- The evaluation of abstract meaning representation structures
- Clustering and hierarchical organization of opinion aspects: a corpus study
- Improving content selection for update summarization with subtopic-enriched sentence ranking functions
- Update summarization for portuguese
- Rearrangement and creation of new corpora for update and compressive summarization tasks for portuguese language
- Semi-supervised never-ending learning in rhetorical relation identification
Informações sobre o DOI: 10.1007/978-3-030-41505-1_22 (Fonte: oaDOI API)
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