Knowledge Management: Learning from Knowledge Engineering

ISBN-13: 9780367455316 / Angielski / Miękka / 2019 / 152 str.

Jay Liebowitz

Opis

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.

Spis treści

Knowledge Management and Knowledge Engineering: Working Together. Knowledge Mapping and Knowledge Acquisition. Knowledge Taxonomy versus Knowledge Ontology and Representation. The Knowledge Management Life Cycle versus the Knowledge Engineering Life Cycle. Knowledge-Based Systems and Knowledge Management. Intelligent Agents and Knowledge Dissemination. Knowledge Discovery and Knowledge Management. People and Culture: Lessons Learned from AI to Help Knowledge Management. Implementing Knowledge Management Strategies. Expert Systems and AI: Integral Parts of Knowledge Management. Appendix A: A Knowledge Management Strategy for the U.S. Federal Communications Commission. Appendix B: Knowledge Management Receptivity. Appendix C: Modeling the Intelligence Analysis Process for Intelligent User Agent Development. Appendix D: Planning and Scheduling in the Era of Satellite Constellation Missions: A Look Ahead. Index.

O autorze

Liebowitz, Jay