Knowledge Engineering For Modern Information Systems
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Knowledge Engineering for Modern Information Systems
Author: Anand Sharma
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2022-01-19
Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledgebased systems. KE is the process of imitating how a human expert in a specific domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent findings and innovative research in the information system and KE domain. Highlighting the challenges and difficulties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artifi cial Intelligence, Cognitive Neuro - science, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will find this book a valuable source of ideas and guidance.
Advances in Knowledge-based and Intelligent Information and Engineering Systems
In this 2012 edition of Advances in Knowledge-Based and Intelligent Information and Engineering Systems the latest innovations and advances in Intelligent Systems and related areas are presented by leading experts from all over the world. The 228 papers that are included cover a wide range of topics. One emphasis is on Information Processing, which has become a pervasive phenomenon in our civilization. While the majority of Information Processing is becoming intelligent in a very broad sense, major research in Semantics, Artificial Intelligence and Knowledge Engineering supports the domain specific applications that are becoming more and more present in our everyday living. Ontologies play a major role in the development of Knowledge Engineering in various domains, from Semantic Web down to the design of specific Decision Support Systems. Research on Ontologies and their applications is a highly active front of current Computational Intelligence science that is addressed here. Other subjects in this volume are modern Machine Learning, Lattice Computing and Mathematical Morphology.The wide scope and high quality of these contributions clearly show that knowledge engineering is a continuous living and evolving set of technologies aimed at improving the design and understanding of systems and their relations with humans.
Knowledge Engineering and Management
Prologue: The Value of Knowledge -- 2. Knowledge-Engineering Basics -- 3. The Task and Its Organizational Context -- 4. Knowledge Management -- 5. Knowledge Model Components -- 6. Template Knowledge Models -- 7. Knowledge Model Construction -- 8. Knowledge-Elicitation Techniques -- 9. Modelling Communication Aspects -- 10. Case Study: The Housing Application -- 11. Designing Knowledge Systems -- 12. Knowledge-System Implementation -- 13. Advanced Knowledge Modelling -- 14. UML Notations Used in Common KADS -- 15. Project Management.