Applying Knowledge Management

Techniques for Building Corporate Memories

Ian Watson

• Verlag: Morgan Kaufmann
• Jahr: 2003
• ISBN:
  9780080499277
• Thema: Informatica
• Thema: Intelligenza artificiale (IA) e semantica

The wholesale capture and distribution of knowledge over the last thirty years has created an unprecedented need for organizations to manage their knowledge assets. Knowledge Management (KM) addresses this need by helping an organization to leverage its information resources and knowledge assets by "remembering" and applying its experience. KM involves the acquisition, storage, retrieval, application, generation, and review of the knowledge assets of an organization in a controlled way. Today, organizations are applying KM throughout their systems, from information management to marketing to human resources. Applying Knowledge Management: Techniques for Building Corporate Memories examines why case-based reasoning (CBR) is so well suited for KM. CBR can be used to adapt solutions originally designed to solve problems in the past, to address new problems faced by the organization. This book clearly demonstrates how CBR can be successfully applied to KM problems by presenting several in-depth case-studies. Ian Watson, a well-known researcher in case-based reasoning and author of the introductory book, Applying CBR: Techniques for Enterprise Systems has written this book specifically for IT managers and knowledge management system developers.* Provides 7 real-world applications of knowledge management systems that use case-based reasoning techniques.
* Presents the technical information needed to implement a knowledge management system.
* Offers insights into the development of commercial KM CBR applications
* Includes information on CBR software vendors, CBR consultants and value added resellers

Inhaltsverzeichnis

• Front Cover
• Applying Knowledge Management
• Copyright Page
• Contents
• Preface
• Part I: Corporate Memory
• Part II: Case Studies
• Part III: Conclusion
• Appendix: Resources
• Index