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'Knowledge Management System (KM System)' is a system for managing knowledge in organizations, supporting creation, capture, storage and dissemination of expertise and knowledge.

The idea of a KM system is to enable employees to have access to the organization's knowledge of facts, sources of information, and solutions. For example, an engineer could know the metallurgical composition of an alloy that reduces sound in gear systems. Sharing this organization wide can lead to more effective engine design and it could also lead to ideas for new or improved equipment.

A KM system could be any of the following: 1. Document based i.e. any technology that permits creation/management/sharing of formatted documents such as Lotus Notes, web, distributed databases etc. 2. Ontology based: these are similar to document technologies in the sense that a system of terminologies (i.e. ontology) are used to summarize the document e.g. Author, Subj, Organization etc. as in DAML & other XML based ontologies 3. Based on AI technologies which use a customized representation scheme to represent the problem domain. In one research project, RST theory was utilized to represent automotive problems (Rosner et al. 1998).

Except for the first case, technologies based on ontologies and AI are still under development. The KM development process proceeds as follows:

    1. Map available knowledge
    2. Identify gaps
    3. Generate/capture knowledge
    4. Implement

'Benefits of KM Systems'

KM systems have become more and more popular as technologies continue to evolve. Some of the advantages of KM systems are:

  1.   Sharing of valuable organizational knowledge.
 
  2.   Avoids re-inventing the wheel, reduces redundant work.
  3.   Reduces training time for new employees
  4.   Frees the experts
  5.   Retention of Intellectual Property even after the employee leaves.

This article was originally based on material from the Free On-line Dictionary of Computing, which is licensed under the GFDL.

http://www.management.com.ua/strategy/str109.html

Rosner, D.., Grote, B., Hartman, K, Hofling, B, Guericke, O. (1998) From natural language documents to sharable product knowledge: a knowledge engineering approach. in Borghoff Uwe M., and Pareschi, Remo (Eds.). Information technology for knowledge management. Springer Verlag, pp 35-51.

Langton, N & Robbins, S. (2006). Organizational Behaviour (Fourth Canadian Edition). Toronton, Ontario: Pearson Prentice Hall.

Maier, R (2004): Knowledge Management Systems: Information And Communication Technologies for Knowledge Management. 2nd edition, Berlin: Springer.

Rhetorical Structure Theory (assumed from the reference of RST Theory above) http://acl.ldc.upenn.edu/W/W01/W01-1605.pdf

The RST site at http://www.sfu.ca/rst/ run by Bill Mann