Knowledge Management : Learning from Knowledge Engineering

Jay Liebowitz

ISBN 10: 0367455315 / ISBN 13: 9780367455316

Published by CRC Press, 2019

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Knowledge Management (KM) is strongly rooted in the discipline of Knowledge Engineering (KE), which in turn grew partly out of the artificial intelligence field. Despite their close relationship, however, many KM specialists have failed to fully recognize the synergy or acknowledge the power that KE methodologies, techniques, and tools hold for enhancing the state of the art in Knowledge Management.Knowledge Management: Learning from Knowledge Engineering addresses this vacuum. It gives concise, practical information and insights drawn from the author's many years of experience in the fields of expert systems and Knowledge Management. Based upon research, analyses, and illustrative case studies, this is the first book to integrate the theory and practice of artificial intelligence and expert systems with the current organizational and strategic aspects of Knowledge Management.The time has come for Knowledge Management professionals to appreciate the synergy between their work and the work of their counterparts in Knowledge Engineering. Knowledge Management: Learning from Knowledge Engineering is the ideal starting point for those in KM to learn from and exploit advances in that field, and thereby advance their own.

Seller Inventory # 9780367455316

Bibliographic Details

• Title: Knowledge Management : Learning from Knowledge Engineering
• Publisher: CRC Press
• Publication Date: 2019
• Language: English
• ISBN 10: 0367455315
• ISBN 13: 9780367455316
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 234W x 156H x 8D millimeters 234 millimeters width by 156 millimeters height by 8 millimeters depth
• Weight: 237 grams

About this title

Synopsis

Knowledge Management (KM) is strongly rooted in the discipline of Knowledge Engineering (KE), which in turn grew partly out of the artificial intelligence field. Despite their close relationship, however, many KM specialists have failed to fully recognize the synergy or acknowledge the power that KE methodologies, techniques, and tools hold for enhancing the state of the art in Knowledge Management. Knowledge Management: Learning from Knowledge Engineering addresses this vacuum. It gives concise, practical information and insights drawn from the author's many years of experience in the fields of expert systems and Knowledge Management. Based upon research, analyses, and illustrative case studies, this is the first book to integrate the theory and practice of artificial intelligence and expert systems with the current organizational and strategic aspects of Knowledge Management. The time has come for Knowledge Management professionals to appreciate the synergy between their work and the work of their counterparts in Knowledge Engineering. Knowledge Management: Learning from Knowledge Engineering is the ideal starting point for those in KM to learn from and exploit advances in that field, and thereby advance their own.

About the Author

Liebowitz, Jay