Bi-directional LSTM-CNNs-CRF for Italian Sequence Labeling and Multi-Task Learning
In this paper, we propose a Deep Learning architecture for several Italian Natural Language Processing tasks 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. This architecture provided state of...
Guardado en:
| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Accademia University Press
2017
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/7d12c46b5d31477aacc399f811980343 |
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