Knowledge engineering for modern information systems methods, models and tools edited by Anand Sharma, Sandeep Kautish, Prateek Agrawal, Vishu Madaan, Charu Gupta, Saurav Nanda.
Material type:
TextSeries: De Gruyter series on smart computing applications ; v. 3.Publisher: Berlin ; Boston Walter de Gruyter GmbH, [2022]Description: 1 online resource (vi, 232 pages) illustrations (chiefly color)ISBN: 9783110713633; 3110713632; 9783110713695; 3110713691Subject(s): Information resources management | Information Management | Gestion de l'information | Information resources managementGenre/Form: EBSCO eBooks | Electronic books. | Electronic books. DDC classification: 658.4038 LOC classification: T58.64 | .K56 2022Online resources: EBSCOhost Summary: Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledge based 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, Artificial Intelligence, Cognitive Neuroscience, 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.
Includes bibliographical references and index.
Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledge based 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, Artificial Intelligence, Cognitive Neuroscience, 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.
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