A Review on Application of Deep Learning in Natural Language Processing

P. Kshirsagar, D. H. Reddy, Mallika Dhingra, Dharmesh Dhabliya, Ankur Gupta
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Abstract

Natural Language Processing (NLP) is a developing method utilized in building different sorts of Artificial Intelligence (AI) that is available in today’s time. More intellectual applications will tend to be a primary goal for ongoing and upcoming research. The requirement and desire for data-driven strategies for automatic semantic analysis have risen as a result of recent improvements in processing capacity as well as the accessibility of enormous several linguistic records. A boom in the applications throughout the previous several years of deep learning approaches has advanced the area of natural language processing. This review offers a succinct summary of deep learning architectures and techniques as well as a basic introduction to the area. Our goal is to develop a theoretical study of numerous sectors where NLP may have a significant impact and completely alter the situation with its automated approaches. Everyone is interested in investing in it since it is a hot issue. An in-depth investigation of NLP and its field is used to create these applications. Natural language processing (NLP) trends and its constituent parts are covered in the introduction to this article before it discusses applications for NLP, its emergence, and related issues.
深度学习在自然语言处理中的应用综述
自然语言处理(NLP)是一种用于构建当今可用的各种人工智能(AI)的发展方法。更多的智能应用将成为正在进行和即将进行的研究的主要目标。由于最近处理能力的提高以及大量语言记录的可访问性,对自动语义分析的数据驱动策略的需求和愿望已经上升。在过去的几年里,深度学习方法的应用蓬勃发展,推动了自然语言处理领域的发展。这篇综述提供了深度学习架构和技术的简洁总结,以及对该领域的基本介绍。我们的目标是对许多领域进行理论研究,在这些领域,NLP可能会产生重大影响,并通过其自动化方法完全改变情况。每个人都有兴趣投资它,因为它是一个热点问题。对自然语言处理及其领域的深入研究用于创建这些应用程序。在讨论自然语言处理(NLP)的应用、它的出现和相关问题之前,本文的引言部分涵盖了自然语言处理(NLP)的趋势及其组成部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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