Advanced Concepts Methods And Applications In Semantic Computing
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Advanced Concepts, Methods, and Applications in Semantic Computing
Semantic computing is critical for the development of semantic systems and applications that must utilize semantic analysis, semantic description, semantic interfaces, and semantic integration of data and services to deliver their objectives. Semantic computing has enormous capabilities to enhance the efficiency and throughput of systems that are based on key emerging concepts and technologies such as semantic web, internet of things, blockchain technology, and knowledge graphs. Thus, research that expounds advanced concepts, methods, technologies, and applications of semantic computing for solving challenges in real-world domains is vital. Advanced Concepts, Methods, and Applications in Semantic Computing is a scholarly reference book that provides a sound theoretical foundation for the application of semantic methods, concepts, and technologies for practical problem solving. It is designed as a comprehensive and reliable resource on how semantic-oriented approaches can be used to aid new emergent technologies and tackle real-world problems. Covering topics that include deep learning, machine learning, blockchain technology, and semantic web services, this book is ideal for professionals, academicians, researchers, and students working in the field of semantic computing in various disciplines, including but not limited to software engineering, systems engineering, knowledge engineering, electronic commerce, computer science, and information technology.
Semantics with Applications: An Appetizer
Semantics will play an important role in the future development of software systems and domain-specific languages. This book provides a needed introductory presentation of the fundamental ideas behind these approaches, stresses their relationship by formulating and proving the relevant theorems, and illustrates the applications of semantics in computer science. Historically important application areas are presented together with some exciting potential applications. The text investigates the relationship between various methods and describes some of the main ideas used, illustrating these by means of interesting applications. The book provides a rigorous introduction to the main approaches to formal semantics of programming languages.
Machine Learning Applications in Non-Conventional Machining Processes
Traditional machining has many limitations in today’s technology-driven world, which has caused industrial professionals to begin implementing various optimization techniques within their machining processes. The application of methods including machine learning and genetic algorithms has recently transformed the manufacturing industry and created countless opportunities in non-traditional machining methods. Significant research in this area, however, is still considerably lacking. Machine Learning Applications in Non-Conventional Machining Processes is a collection of innovative research on the advancement of intelligent technology in industrial environments and its applications within the manufacturing field. While highlighting topics including evolutionary algorithms, micro-machining, and artificial neural networks, this book is ideally designed for researchers, academicians, engineers, managers, developers, practitioners, industrialists, and students seeking current research on intelligence-based machining processes in today’s technology-driven market.