Name
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/SNAMS.2018.8554782 | 2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS) |
Keywords | DocType | ISBN |
deep neural networks,Named entity Recognition,Portuguese texts,deep learning,Named Entities Recognition,Portuguese datasets,annotated data,NER models,nonannotated data,bootstrapping approach,raw textual data | Conference | 978-1-5386-9589-0 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ivo Fernandes | 1 | 0 | 0.34 |
| Henrique Lopes Cardoso | 2 | 223 | 34.02 |
| Eugénio Oliveira | 3 | 974 | 111.00 |