Introduction to Natural Language Processing: Exploring Techniques, Applications, and Challenges

This book provides a thorough and comprehensive introduction to natural language processing (NLP), a critical field at the intersection of artificial intelligence and computational linguistics. It explores key techniques such as sentiment analysis, which enables the detection of emotional tone in text, machine translation, facilitating the conversion of text between languages, and named entity recognition (NER), which identifies and classifies entities like names, dates, and locations within text data.

The book delves into deep learning advancements, particularly the use of neural networks such as transformers and recurrent models, which have revolutionized NLP applications. Readers will gain insights into how these models drive innovations in areas such as text classification, language generation, and speech recognition.

In addition to technical concepts, the book also addresses the ethical considerations surrounding NLP, emphasizing the responsible use of AI technologies to mitigate issues like bias, misinformation, and privacy concerns. Practical case studies and real-world examples are included to illustrate how NLP is applied in various sectors, including healthcare, finance, and customer service.

This book is an invaluable resource for students, researchers, and industry professionals seeking to understand the foundational concepts, cutting-edge advancements, and broader implications of NLP, equipping them with the knowledge to innovate and apply these technologies effectively in their respective fields.

1147360001
Introduction to Natural Language Processing: Exploring Techniques, Applications, and Challenges

This book provides a thorough and comprehensive introduction to natural language processing (NLP), a critical field at the intersection of artificial intelligence and computational linguistics. It explores key techniques such as sentiment analysis, which enables the detection of emotional tone in text, machine translation, facilitating the conversion of text between languages, and named entity recognition (NER), which identifies and classifies entities like names, dates, and locations within text data.

The book delves into deep learning advancements, particularly the use of neural networks such as transformers and recurrent models, which have revolutionized NLP applications. Readers will gain insights into how these models drive innovations in areas such as text classification, language generation, and speech recognition.

In addition to technical concepts, the book also addresses the ethical considerations surrounding NLP, emphasizing the responsible use of AI technologies to mitigate issues like bias, misinformation, and privacy concerns. Practical case studies and real-world examples are included to illustrate how NLP is applied in various sectors, including healthcare, finance, and customer service.

This book is an invaluable resource for students, researchers, and industry professionals seeking to understand the foundational concepts, cutting-edge advancements, and broader implications of NLP, equipping them with the knowledge to innovate and apply these technologies effectively in their respective fields.

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Introduction to Natural Language Processing: Exploring Techniques, Applications, and Challenges

Introduction to Natural Language Processing: Exploring Techniques, Applications, and Challenges

Introduction to Natural Language Processing: Exploring Techniques, Applications, and Challenges

Introduction to Natural Language Processing: Exploring Techniques, Applications, and Challenges

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Overview

This book provides a thorough and comprehensive introduction to natural language processing (NLP), a critical field at the intersection of artificial intelligence and computational linguistics. It explores key techniques such as sentiment analysis, which enables the detection of emotional tone in text, machine translation, facilitating the conversion of text between languages, and named entity recognition (NER), which identifies and classifies entities like names, dates, and locations within text data.

The book delves into deep learning advancements, particularly the use of neural networks such as transformers and recurrent models, which have revolutionized NLP applications. Readers will gain insights into how these models drive innovations in areas such as text classification, language generation, and speech recognition.

In addition to technical concepts, the book also addresses the ethical considerations surrounding NLP, emphasizing the responsible use of AI technologies to mitigate issues like bias, misinformation, and privacy concerns. Practical case studies and real-world examples are included to illustrate how NLP is applied in various sectors, including healthcare, finance, and customer service.

This book is an invaluable resource for students, researchers, and industry professionals seeking to understand the foundational concepts, cutting-edge advancements, and broader implications of NLP, equipping them with the knowledge to innovate and apply these technologies effectively in their respective fields.


Product Details

ISBN-13: 9781040422212
Publisher: River Publishers
Publication date: 06/27/2025
Series: River Publishers Series in Rapids in Computing and Information Science and Technology
Sold by: Barnes & Noble
Format: eBook
Pages: 170
File size: 3 MB

About the Author

Dr. Xiaochun Cheng is at Swansea University, Wales, UK, specializing in artificial intelligence, data science, and natural language processing (NLP). With extensive experience in computational linguistics, Dr. Cheng has published numerous papers in top-tier journals and actively contributes to advancing AI research.

Dr. Preethi Nanjundan is an Associate Professor and Research head at CHRIST University, Pune Lavasa Campus, India, with 20 years of experience in research and teaching. Her expertise spans machine learning, neural networks, and NLP, and she has published over 40 papers and several books. She is also a lifetime member of professional bodies like IEEE and CSI.

Dr. Jossy P George is a distinguished professor in the Department of Data Science and the Dean and Director at CHRIST University, Delhi NCR Campus, India. His research interests include data analytics, machine learning, and NLP, with significant contributions to both academia and industry. He plays a pivotal role in mentoring students and leading collaborative research projects.

Table of Contents

1. Introduction 2. Parsing and Syntax 3. Smoothed Estimation and Language Modelling 4. Semantic Analysis and Discourse Processing 5. Natural Language Generation and Machine Translation 6. Information Retrieval and Lexical Resurces 7. Unsupervised Methods in NLP 8. Summary 9. Conclusion

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