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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書誌詳細

主要な著者:	Hyein Seo, Sangkeun Jung, Taewook Hwang, Hyunji Kim, Yoon-Hyung Roh
フォーマット:	Artigo
言語:	Inglês
出版事項:	IEEE 2021-01-01
シリーズ:	IEEE Access
主題:	Syntax vector learning syntax similarity syntax representation natural language understanding transformer deep learning
オンライン･アクセス:	https://ieeexplore.ieee.org/document/9448015/
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