Case-Based Problem Solving for Knowledge Management Systems

Case-Based Problem Solving for Knowledge Management SystemsCase-Based Problem Solving for Knowledge Management Systems

Dr. Irma Becerra-Fernandez
Florida International University, Decision Sciences and Information Systems, College of Business Administration, BA 256A Miami, FL 33199,, (305) 348-3278, (305) 348-3476 fax

Dr. David W. Aha
Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, Washington, DC 20375,, (202) 404-4940, (202) 767-3172 fax


Case Based Reasoning (CBR) is an intelligent systems methodology that enables information managers to increase efficiency and reduce cost by substantially automating processes (i.e., diagnosis, scheduling, or design). By identifying and ranking the relevance between a new case and previously encountered cases (i.e., stored in the case base), CBR systems can capture and share all of an organization’s related knowledge capital for future use, and knowledge recycling can optimize resources spent on research and development. Unfamiliar cases are solved and documented by retrieving and adapting solutions from similar stored cases. Sample applications include a proposed knowledge system designed to enhance the NASA-KSC Shuttle Processing Out-of-Family Disposition process, which addresses any operation or performance outside expected range or one that has not previously been experienced. CBR technology can yield productive results by transforming problem report and interim problem report related documentation into explicit knowledge that can be reused to obtain solutions for new anomalies. Applying CBR technology to the Out-of-Family Disposition process can transform the organization into a learning organization that continues to grow in intellectual capital and related applied knowledge. This paper discusses the application of the NaCoDAE Conversational CBR (CCBR) system for this process. NaCoDAE is a software package developed at the Naval Research Laboratory. It uses CCBR technology to store cases, questions, and actions; and has a built-in method that efficiently searches for the most relevant cases.

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