By Ian Watson
The wholesale catch and distribution of information over the past thirty years has created an exceptional desire for enterprises to control their wisdom resources. wisdom administration (KM) addresses this desire through aiding a firm to leverage its info assets and data resources via "remembering" and utilizing its event. KM consists of the purchase, garage, retrieval, software, new release, and evaluation of the information resources of a company in a managed means. at the present time, agencies are using KM all through their platforms, from details administration to advertising to human assets. utilizing wisdom administration: recommendations for construction company thoughts examines why case-based reasoning (CBR) is so well matched for KM. CBR can be utilized to evolve ideas initially designed to resolve difficulties long ago, to handle new difficulties confronted by way of the association. This booklet sincerely demonstrates how CBR will be effectively utilized to KM difficulties through featuring a number of in-depth case-studies. Ian Watson, a well known researcher in case-based reasoning and writer of the introductory e-book, employing CBR: innovations for firm structures has written this publication in particular for IT managers and data administration process builders. * offers 7 real-world purposes of information administration structures that use case-based reasoning techniques.* provides the technical details had to enforce a data administration system.* deals insights into the improvement of industrial KM CBR purposes* comprises details on CBR software program proprietors, CBR experts and cost further resellers
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Extra resources for Applying Knowledge Management: Techniques for Building Corporate Memories (The Morgan Kaufmann Series in Artificial Intelligence)
2, you can see that an individual case is made up of two components—a problem description and a related solution. These can be thought of as residing, respectively, in the problem space and the solution space. The description of a new problem to be solved is positioned in the problem space. 2), and its stored solution is found. 2), and a new solution is created. This conceptual model of CBR assumes that there is a direct one-to-one mapping between the problem and solution spaces. In other words, if a new problem is conceptually “down and to the right” of a known problem, then the new solution may also be “down and to the right” of the retrieved problem’s solution.
2), and a new solution is created. This conceptual model of CBR assumes that there is a direct one-to-one mapping between the problem and solution spaces. In other words, if a new problem is conceptually “down and to the right” of a known problem, then the new solution may also be “down and to the right” of the retrieved problem’s solution. B. ), 1996. Case-Based Reasoning: Experiences, Lessons, & Future Directions. AAAI Press/The MIT Press, Menlo Park, Calif. 34 2 ◆ Understanding Case-Based Reasoning Within a case, you can store most types of data that you would expect to be able to store in a normal database, for example, names, product identifiers, values such as cost or temperature, and textual notes.
The first step in the process was to identify the type of organizational memory that would satisfy Microsoft’s requirements. Project Techniques reviewed the relative merits of each of the main knowledge management technologies: knowledge-based systems, natural language search, and case-based reasoning (CBR). The goal was to ﬁnd a tool that would provide both technical and nontechnical agents with easy, structured access to the knowledge base. This led them to select CBR over the other available technologies.