计算机科学
人工智能
深度学习
自然语言处理
繁荣
领域(数学)
自然语言
自然语言理解
自然(考古学)
数据科学
工程类
数学
环境工程
历史
考古
纯数学
作者
Pravin R. Kshirsagar,Dhoma Harshavardhan Reddy,Mallika Dhingra,Dharmesh Dhabliya,Ankur Gupta
标识
DOI:10.1109/ic3i56241.2022.10073309
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI