Applying Deep Neural Networks to Named Entity Recognition in Portuguese Texts

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2018

Autores

Ivo Fernandes (Autor) Outra; Henrique Lopes Cardoso (Autor) FEUP; Eugénio Oliveira (Autor) FEUP

Ata de Conferência Internacional

Título: 2018 5th International Conference on Social Networks Analysis, Management and Security, SNAMS 2018

Páginas: 284-289

5th International Conference on Social Networks Analysis, Management and Security, SNAMS 2018

15 October 2018 through 18 October 2018

Indexação

ISI Web of Knowledge - 2 Citações

ISI Web of Science

Scopus - 4 Citações

INSPEC

Outras Informações

ID Authenticus: P-00Q-44F

DOI: 10.1109/snams.2018.8554782

Abstract (EN): There is currently few research in using deep learning (DL) applied to Named Entities Recognition (NER) in Portuguese texts. This work exposes some challenges and limitations but also the benefits of applying DL architectures to NER in Portuguese. Four different DL architectures are applied to Portuguese datasets. All architectures are heavily influenced by previous published work in NER applied to English. Annotated data is used to train and test NER models, while non-annotated data is used to train word embeddings, as well as being a key part of a bootstrapping approach, where raw textual data is used to create NER models. © 2018 IEEE.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6