计算机科学
领域(数学)
深度学习
人工智能
自然(考古学)
数据科学
计算语言学
自然语言处理
认知科学
历史
心理学
考古
数学
纯数学
作者
Daniel W. Otter,Julian Richard Medina,Jugal Kalita
出处
期刊:IEEE transactions on neural networks and learning systems
[Institute of Electrical and Electronics Engineers]
日期:2020-04-21
卷期号:32 (2): 604-624
被引量:1228
标识
DOI:10.1109/tnnls.2020.2979670
摘要
Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models. This article provides a brief introduction to the field and a quick overview of deep learning architectures and methods. It then sifts through the plethora of recent studies and summarizes a large assortment of relevant contributions. Analyzed research areas include several core linguistic processing issues in addition to many applications of computational linguistics. A discussion of the current state of the art is then provided along with recommendations for future research in the field.
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