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Overview
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.
Addresses gaps in the literature concerning the methodologies, techniques and tools of knowledge engineering that can enhance the state of the art in knowledge management. Includes illustrative case studies, research, analysis, and an integration of theory and practice of expert systems and artificial intelligence.
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.
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)