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Knowledge Management : Learning From Knowledge Engineering 🔍
Jay Liebowitz Boca Raton: CRC Press, CRC Press (Unlimited), Boca Raton, 2001
英语 [en] · PDF · 7.3MB · 2001 · 📗 未知类型的图书 · 🚀/duxiu/ia · Save
描述
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.
Booknews Addresses the synergies between the disciplines of knowledge engineering and knowledge management, integrating the theory and practice of artificial intelligence and expert systems with the current organizational and strategic aspects of knowledge management. Appendices offer case studies, including a knowledge management strategy for the US Federal Communications Commission and a partial knowledge audit for the US Social Security Administration. Of interest to knowledge managers, knowledge engineers, and directors of intellectual capital, as well as students. Liebowitz teaches information systems at the University of Maryland-Baltimore County. Annotation c. Book News, Inc., Portland, OR (booknews.com)
备选作者
Liebowitz, Jay, 1957-
备用出版商
Auerbach Publishers, Incorporated
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Technomic Publishing Co., Inc.
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Taylor & Francis Group
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Taylor & Francis Ltd
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Chapman & Hall/CRC
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CRC Press LLC
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MyiLibrary
备用出版商
Routledge
备用版本
United Kingdom and Ireland, United Kingdom
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United States, United States of America
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2nd ed, Boca Raton, Fla, ©2003
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Boca Raton (Florida), 2001
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March 28, 2001
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1, 20010328
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1, PS, 2001
备用描述
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 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 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.
备用描述
Knowledge Management: Learning from Knowledge Engineering helps knowledge managers and those involved in knowledge management initiatives improve the current state-of-the-art in developing knowledge management systems. The book explores the need for applying knowledge engineering techniques to knowledge management. The focus is on sharing and leveraging knowledge internally and externally
备用描述
The time has come for Knowledge Management (KM) professionals to appreciate the synergy between their work and the work of their counterparts in Knowledge Engineering (KE). 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
备用描述
1 online resource (139 pages) :
The text attempts to integrate the foundation theory and practice in knowledge engineering, expert systems, and artificial intelligence with the latest thinking on organizational and strategic aspects of the emerging discipline of "knowledge management."
Includes bibliographical references and index
开源日期
2024-11-05
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