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...

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Autores principales: Pierpaolo Basile, Pierluigi Cassotti, Lucia Siciliani, Giovanni Semeraro
Formato: article
Lenguaje:EN
Publicado: Accademia University Press 2017
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Acceso en línea:https://doaj.org/article/7d12c46b5d31477aacc399f811980343
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