自然语言处理中基于图的深度学习

Shikhar Vashishth, N. Yadati, Partha P. Talukdar
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引用次数: 17

摘要

本教程旨在介绍基于图的深度学习技术的最新进展,例如用于自然语言处理(NLP)的图卷积网络(GCNs)。它简要介绍了非欧几里得域(如图)上的深度学习方法,并证明了它们在NLP中的相关性。然后介绍了将基于图的深度学习方法应用于各种NLP任务的最新进展,例如语义角色标记、机器翻译、关系提取等等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Graph-based Deep Learning in Natural Language Processing
This tutorial aims to introduce recent advances in graph-based deep learning techniques such as Graph Convolutional Networks (GCNs) for Natural Language Processing (NLP). It provides a brief introduction to deep learning methods on non-Euclidean domains such as graphs and justifies their relevance in NLP. It then covers recent advances in applying graph-based deep learning methods for various NLP tasks, such as semantic role labeling, machine translation, relationship extraction, and many more.
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