Artificial Intelligence for Natural Language Processing offers a comprehensive exploration of how advanced computational methods are transforming the way machines understand human language. This book delves into the core principles of Natural Language Processing (NLP) through an engaging progression – from fundamental word-level analysis to complex discourse and pragmatic analysis – integrating linguistic theory with cutting-edge AI methodologies. It provides a robust framework for both the theoretical underpinnings and practical applications of NLP, ensuring that readers gain a clear understanding of how computers can effectively process and interpret human language.
What sets this book apart is its methodical structure that guides the reader through each level of language analysis, building upon earlier chapters to culminate in a deep integration of artificial intelligence within NLP systems. The detailed explanations and examples are designed to bridge the gap between abstract theory and real-world application, making it an invaluable resource for anyone looking to grasp the nuances of language processing.
FEATURES
- Provides a step-by-step progression from word-level analysis to syntactic, semantic, and pragmatic processing
- Offers in-depth discussions on word sense disambiguation with illustrative examples
- Presents an exploration of discourse integration and contextual meaning essential for modern NLP models
- Delivers comprehensive coverage of AI applications in NLP, highlighting state-of-the-art computational techniques
- Suggests clear, accessible explanations suitable for both beginners and advanced practitioners
This book is ideal for graduate students, researchers, and professionals in computer science, linguistics, and artificial intelligence. Whether you are a seasoned researcher looking to deepen your understanding or a newcomer eager to explore the field, Artificial Intelligence for Natural Language Processing serves as both an essential academic resource and a practical guide for navigating the evolving landscape of language technology.
Artificial Intelligence for Natural Language Processing offers a comprehensive exploration of how advanced computational methods are transforming the way machines understand human language.
1. Introduction and WordLevel Analysis.
2. Syntactic Analysis.
3.
Semantic Analysis.
4. Discourse and Pragmatic Analysis.
5. Artificial
Intelligence in NLP.
Dhanalekshmi Prasad Yedurkar is a Postdoctoral Researcher at the University of Augsburg, Germany. She is also affiliated to MIT Art, Design and Technology University, Pune, India, as an Associate Professor in the School of Computing. She earned a PhD on the application of digital signal processing and artificial intelligence in anomaly detection of EEG signal. Her current research interests include natural language processing, tool condition monitoring for CNC processes, diagnosis and prognosis of gear monitoring, biomedical signal processing, machine learning, Internet of Things, and image processing.
Ganesh R. Pathak is an Academic and a Researcher with over 26 years of experience bridging academia and industry. He is currently a Professor and Head of the Department of Computer Science and Engineering at the School of Computing, MIT Art, Design and Technology University, Pune.
He earned a PhD in computer science and engineering with his research focused on developing a security framework for wireless sensor networks. He has published 34 research papers in reputed peerreviewed journals and conference proceedings, many of which are indexed in Scopus and SCI. His research and teaching interests focus on artificial intelligence, big data analytics, and cognitive modelling. As a mentor, he guides doctoral candidates in artificial intelligence, data science, cloud computing, and security.
Beyond his research, he is an active contributor to the academic and professional community. He serves on various boards of studies, and he contributes as a reviewer and session chair at national and international conferences. Dr. Pathak also promotes automation and egovernance in educational processes within the university. His efforts extend to skill development through numerous organized workshops, seminars, and faculty development programs, which strengthen his role as an admonitor in academia.
Through his scholarly achievements, project leadership, and engagement in the academic community, Dr. Pathak continues to make contributions to the university and various institutions in advancing technology education and research.
Manisha Galphade is an experienced Academic Professional currently working at the School of Computing, MIT Art, Design and Technology University, Pune. With a teaching career spanning 16 years, she has contributed significantly to the field of education. She teaches subjects including machine learning, database management system, theory of computation, data mining, and many more. Throughout her career, she has authored four conference papers, five journal papers, and three book chapters, showcasing her dedication to research and academic development. She is also pursuing a PhD at Veermata Jijabai Technological Institute, Mumbai, furthering her academic expertise. Her research area is artificial intelligence with research interests in time series analysis, image processing, and signal processing. Passionate about fostering innovation and critical thinking, she strives to inspire students to reach their full potential. Her extensive experience and research contributions reflect her commitment to advancing knowledge and fostering growth in her field.
Thompson Stephan earned a PhD at Pondicherry University, India, in 2018, and he has nearly 7 years of academic experience, complemented by fulltime research and industry expertise. He serves as an Assistant Professor at the Thumbay College of Management and AI in Healthcare, Gulf Medical University, Ajman, United Arab Emirates. Recognized among Stanford/Elseviers Top 2% Scientists globally in both 2023 and 2024, Dr. Thompson has received prestigious accolades, including the Best Researcher Award in 2020 and the Protsahan Research Award in 2023, both from the IEEE Bangalore Section, India. His primary research focus is artificial intelligence with specialized expertise in advancing machine learning, data mining, and metaheuristic optimization. With more than 80 Scopusindexed publications, including 48 in SCIindexed journals, Thompsons work has garnered significant recognition. He actively contributes as a book editor and reviewer for esteemed international journals, with publications on leading platforms such as IEEE, Elsevier, Taylor & Francis, and Springer.
