 | Knowledge Management: Learning from Knowledge Engineering Subjects: Computer Science; Economics Finance Business & Industry; Engineering & Technology; Management of IT; Business Management and Marketing; Engineering Management; 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 enh Dr. Jay Liebowitz is the Robert W. Deutsch Distinguished Professor of Information Systems at the University of Maryland-Baltimore County (UMBC) in Catonsville, Maryland. He was previously Professor of Management Science in the School of Business and Public Management at George Washington University and has served as the Chair of Artificial Intelligence at the U.S. Army War College. He is the founder and Editor-in-Chief of Expert Systems with Applications: An International Journal (published by Elsevier) and Failure and Lessons Learned in Information Technology Management: An International Journal. He is the founder and chair of the World Congress on Expert Systems, where typically 40 to 45 countries are represented. Dr. Liebowitz was selected as the Computer Educator of the Year by the International Association for Computer Information Systems. He was a Fulbright Scholar in Canada, the IEEE-USA Federal Communications Commission Executive Fellow, and holds a number of other honors. He has published 28 books and over 220 papers dealing with expert systems, knowledge management, and information systems management. He can be reached at liebowit@umbc.edu. |
