Applying Knowledge Management: Techniques for Building by Ian Watson

By Ian Watson

The wholesale trap and distribution of data over the past thirty years has created an extraordinary want for firms to control their wisdom resources. wisdom administration (KM) addresses this desire through supporting a firm to leverage its details assets and information resources by way of "remembering" and using its event. KM comprises the purchase, garage, retrieval, software, iteration, and evaluation of the data resources of a company in a managed manner. this day, agencies are employing KM all through their structures, from info administration to advertising to human assets. employing wisdom administration: recommendations for construction company stories examines why case-based reasoning (CBR) is so compatible for KM. CBR can be utilized to conform ideas initially designed to unravel difficulties some time past, to handle new difficulties confronted by way of the association. This e-book truly demonstrates how CBR should be effectively utilized to KM difficulties through offering numerous in-depth case-studies. Ian Watson, a well known researcher in case-based reasoning and writer of the introductory ebook, employing CBR: suggestions for firm structures has written this ebook in particular for IT managers and information administration method builders. * offers 7 real-world purposes of information administration platforms that use case-based reasoning options. * provides the technical info had to enforce a data administration method. * deals insights into the advance of business KM CBR purposes * comprises details on CBR software program proprietors, CBR specialists and cost additional resellers

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30 2 ◆ Understanding Case-Based Reasoning Patient Ref #: Patient Name: Address: Next of Kin: Photo: 1024 John Doe 12 Elm Street Jane Doe Unindexed features Age: Sex: Weight: Height: Blood Type: ... 53 Male 225 lbs 5’11” A neg. 1 Indexed and unindexed case features. Let us use the bank loan example again. Some information provided by prospective clients to you is clearly not predictive of their likely success at repaying a loan, such as their name or telephone number. Some information may be predictive, such as their address— if they live in an upmarket suburb, you might assume they are financially stable.

However, knowledge is not always tangible like a patent or other intellectual property; much of it is difficult, perhaps impossible to codify. The key points you should take away from this chapter are that: ■ Knowledge is not static; it evolves. Any knowledge management system must be able to support the acquisition, analysis, preservation, and reuse of knowledge as a continual cyclical process. 10 Conclusion ■ 21 Knowledge exists in two forms: explicit knowledge that can be codified and tacit knowledge that cannot always be codified.

Thus, when developing a heterogeneous case base, it may be fruitless to imagine all possible features. Instead, developers must rely on historical records. If these are not available, developing a reliable 1 This process is described in the case study in Chapter 7. 6 Case Storage and Indexing 29 case base will be difficult and will require extensive knowledge engineering. The case studies that follow this chapter will highlight the distinction between these two types of case bases and the ease or difficulty of initially acquiring cases.

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