Bi-directional LSTM-CNNs-CRF for Italian Sequence Labeling
In this paper, we propose a Deep Learning architecture for sequence labeling based on a state of the art model that exploits both word- and character-level representations through the combination of bidirectional LSTM, CNN and CRF. We evaluate the proposed method on three Natural Language Processing...
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | Chapter |
| Lenguaje: | Inglês |
| Publicado: |
Accademia University Press
2017
|
| Acceso en línea: | https://doi.org/10.4000/books.aaccademia.2339 https://hdl.handle.net/20.500.13089/1d7i https://books.openedition.org/aaccademia/2339 |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|