Knowledge Management

Learning from Knowledge Engineering

By: Jay Liebowitz

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Paperback | 2 December 2019 | Edition Number 1

At a Glance

Paperback
148 Pages

Dimensions(cm)
23.39 x 15.6 x 0.81

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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.

Industry Reviews

"This book represents an important milestone in the integration of soft and hard aspects of the emerging discipline of Knowledge Managementthe first serious attempt to synthesize foundation theory and practice in Knowledge Engineering, expert systems, and artificial intelligence with the latest thinking on organizational and strategic aspects of Knowledge Managementa must-readI am delighted to recommend this book to my peers in industry and academia." - Yogesh Malhotra, Chairman and CKO, @Brint.com LLC

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