Syntax Vector Learning Using Correspondence for Natural Language Understanding

Natural language understanding (NLU) is a core technique for implementing natural user interfaces. In this study, we propose a neural network architecture to learn syntax vector representation by employing the correspondence between texts and syntactic structures. For representing the syntactic stru...

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Bibliografiske detaljer

Principais autores:	Hyein Seo, Sangkeun Jung, Taewook Hwang, Hyunji Kim, Yoon-Hyung Roh
Format:	Artigo
Sprog:	Inglês
Udgivet:	IEEE 2021-01-01
Serier:	IEEE Access
Fag:	Syntax vector learning syntax similarity syntax representation natural language understanding transformer deep learning
Online adgang:	https://ieeexplore.ieee.org/document/9448015/
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