Applying Knowledge Management: Techniques for Building - download pdf or read online

By Ian Watson

ISBN-10: 0585448183

ISBN-13: 9780585448183

ISBN-10: 1558607609

ISBN-13: 9781558607606

The wholesale seize and distribution of information over the past thirty years has created an remarkable desire for companies to control their wisdom resources. wisdom administration (KM) addresses this want by way of assisting a firm to leverage its info assets and data resources by means of "remembering" and utilising its event. KM consists of the purchase, garage, retrieval, software, new release, and assessment of the information resources of a company in a managed means. at the present time, companies are employing KM all through their structures, from info administration to advertising to human assets. utilising wisdom administration: options for construction company stories examines why case-based reasoning (CBR) is so like minded for KM. CBR can be utilized to conform ideas initially designed to resolve difficulties some time past, to deal with new difficulties confronted via the association. This e-book essentially demonstrates how CBR will be effectively utilized to KM difficulties by way of offering a number of in-depth case-studies. Ian Watson, a widely known researcher in case-based reasoning and writer of the introductory booklet, using CBR: thoughts for firm platforms has written this ebook particularly for IT managers and data administration approach builders. * presents 7 real-world purposes of data administration platforms that use case-based reasoning techniques.* offers the technical details had to enforce a data administration system.* deals insights into the improvement of business KM CBR purposes* contains info on CBR software program owners, CBR experts and cost further resellers

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Additional info for Applying Knowledge Management: Techniques for Building Corporate Memories (The Morgan Kaufmann Series in Artificial Intelligence)

Example text

To many people in the knowledge management community, it is wrong to attempt to codify (that is, to make explicit) all knowledge, and attempts to do so result in much tacit knowledge being lost. Thus, the knowledge representations used by a knowledge management system must be flexible. The rigid formalisms of rule-based expert systems from the 1980s are too restrictive to handle tacit knowledge. The more discursive representation of a library of case histories, such as those employed by case-based reasoning systems, may be better able to deal with tacit knowledge; although you should recognize that no formalization exists that can adequately capture all tacit knowledge.

Revise or adapt that knowledge in light of its use if necessary. Review the new knowledge to see if it is worth retaining. Retain the new knowledge if indicated by step 4. Refine the knowledge in the knowledge memory as necessary. 4, as follows: 7 Watson, I. (2000). ” In Expert Update, Vol. 3 No. 2, pp. 36–38. ISSN 14654091. , & Schank, R. (1989). Inside Case-Based Reasoning. Erlbaum, Northvale, NJ. ” Checkland, P. and Scholes, J. (1990). Soft Systems Methodology in Action, Wiley, New York. 5 The CBR-cycle.

3. 4. 5. 6. Retrieve Reuse Revise Review Retain Refine Each of these will be described in turn, but first you need to understand what it is that is being retrieved, reused, revised, and so on— namely, cases. 5 Cases Cases are records of experiences that contain knowledge, which can be both explicit and tacit. For example, they can be cases in the legal sense, they can be case histories of patients in the medical sense, details of bank loans, or descriptions of equipment troubleshooting situations.

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Applying Knowledge Management: Techniques for Building Corporate Memories (The Morgan Kaufmann Series in Artificial Intelligence) by Ian Watson


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