Knowledge management learning from knowledge engineering

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...

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Bibliographic Details
Main Author: Lebowitz, Jay 1957- (Author)
Format: Unknown
Language:English
Published: Boca Raton CRC Press 2001
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Online Access:Click Here to View Status and Holdings.
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504 # # |a Includes bibliographical references and index 
520 # # |a 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. 
650 # 0 |a Expert systems (Computer science) 
650 # 0 |a Knowledge management 
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