Case-Based Problem Solving for Knowledge Management Systems

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 organizationOs related knowledge capital for future use, and knowledge recycling can optimize resources spent o n 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 t o store cases, questions, and actions; and has a built-in method that efficiently searches for the most relevant cases.