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Author(s): Ivo Fernandes
Henrique Lopes Cardoso
Eugénio Oliveira
Title: Applying Deep Neural Networks to Named Entity Recognition in Portuguese Texts
Issue Date: 2018
Abstract: 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. (c) 2018 IEEE.
Source: 2018 5th International Conference on Social Networks Analysis, Management and Security, SNAMS 2018
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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