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2021 | Buch

Global Trends Kapitel lesen Erstes Kapitel lesen

The Development of Natural Language Processing

Research on the Development of Electronic Information Engineering Technology in China

verfasst von: Chinese Academy of Engineering

Verlag: Springer Singapore

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book is a part of the Blue Book series “Research on the Development of Electronic Information Engineering Technology in China”, which explores the cutting edge of natural language processing (NLP) studies.
The research objects of natural language processing are evolved from words, phrases, and sentences to text, and research directions are from language analysis, language understanding, language generation, knowledge graphs, machine translation, to deep semantic understanding, and beyond. This is in line with the development trend of applications. And for another typical NLP application machine translation, from text translation, to voice and image translation, now simultaneous interpretation, progress of technology makes the application of machine translation deeper and wider into diverse industries.
This book is intended for researchers and industrial staffs who have been following the current situation and future trends of the natural language processing. Meanwhile, it also bears high value of reference for experts, scholars, and technical and engineering managers of different levels and different fields.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Global Trends
Abstract
Language is the method of communication and the carrier of human thoughts and knowledge. It fully expresses both human emotions and cognitions. Language implies a large amount of knowledge that mankind has continuously learned about the world in practice, and it is one of the important signs of human intelligence.
Chinese Academy of Engineering
Chapter 2. Development Status in China
Abstract
In the process of technological revolution and industrial transformation driven by the new generation of artificial intelligence, China highly values and promotes the healthy development of AI. In recent years, NLP, as one of the core fields of AI research, has rapidly developed in all respects. For example, it maintains the leading position in fields of knowledge graph construction and application, semantic analysis, machine translation, and others, and meanwhile, it continues to narrow the gap with the world’s leading level in fundamental theories and underlying technologies. In terms of technology application and industry promotion, China is in the first echelon of the world. Innovative technologies drive industrial development, and applications and products such as intelligent search, machine translation, and smart speakers have penetrated into people’s daily life, which not only changes the way people obtain information, knowledge, and service, but also further promotes the intelligent development of social economy.
Chinese Academy of Engineering
Chapter 3. Trends and Highlights in China
Abstract
Great progress has been witnessed in KG technology and applications. KG is now one of the most representative technologies of knowledge engineering in the era of big data and has been put into large-scale implementation in Search, Question Answering, and other simple scenarios. China’s strong concern and continued commitment to innovation in KG technology and applications in the past few years have resulted in a lot of progress and breakthroughs. Key issues and highlights will be elaborated on from both a technology and application perspective.
Chinese Academy of Engineering
Chapter 4. Trends and Prospects
Abstract
An inter-discipline of linguistic, computer science, and cognitive psychology, NLP is one of the most challenging subjects in AI. In recent years, NLP has been widely applied in various scenarios, which has posed new challenges to NLP. Generally speaking, current breakthroughs in NLP were brought by big data and deep learning. In particular, it was thanks to the progress of pre-training that large-scale unlabeled data could be used to improve the understanding ability of models. However, over-dependence on big data, interpretability, lack of deep understanding and reasoning, and low tolerance to noises remain problems for models.
Chinese Academy of Engineering
Backmatter
Metadaten
Titel
The Development of Natural Language Processing
verfasst von
Chinese Academy of Engineering
Copyright-Jahr
2021
Verlag
Springer Singapore
Electronic ISBN
978-981-16-1986-1
Print ISBN
978-981-16-1985-4
DOI
https://doi.org/10.1007/978-981-16-1986-1

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