For graduate-level courses in Knowledge Management and Decision Support Systems.This 17 chapter, brand new text presents a multiperspective approach to KM (Knowledge Management): it spans electrical engineering, artificial intelligence, information systems, and business. Comprehensive yet clearly and concisely written, Knowledge Management is simultaneously strong in managerial, technical, and systemic aspects of KM, providing students with the right combination of theory, technology, and solutions.
I. PRINCIPLES OF KNOWLEDGE MANAGEMENT. 1. Introducing Knowledge Management. 2. The Nature of Knowledge. 3. Knowledge Management Solutions. 4. Organizational Impacts of Knowledge Management. 5. Factors Influencing Knowledge Management. 6. Knowledge Management Assessment of an Organization. II. TECHNOLOGIES FOR KNOWLEDGE MANAGEMENT. 7. Technologies to Manage Knowledge: Artificial Intelligence. 8. Preserving and Applying Human Expertise: Knowledge-Based Systems. 9. Using Past History Explicitly as Knowledge: Case-Based Systems. 10. Knowledge Elicitation-Converting Tacit Knowledge to Explicit. 11. The Computer as a Medium for Sharing Knowledge. 12. Discovering New Knowledge-Data Mining. III. KNOWLEDGE MANAGEMENT SYSTEMS. 13. Knowledge Discovery: Systems that Create Knowledge. 14. Knowledge Capture Systems: Systems that Preserve and Formalize Knowledge. 15. Knowledge Sharing Systems: Systems that Organize and Distribute Knowledge. 16. Knowledge Application Systems: Systems that Utilize Knowledge. IV. THE FUTURE OF KNOWLEDGE MANAGEMENT. Epilogue. The Future of Knowledge Management. Appendix A: Basic Computer Networks. Glossary.