Case-Based Problem Solving for Knowledge Management Systems

Irma Becerra-Fernandez, Florida International University and David W. Aha, Naval Research Laboratory

This paper describes the implementation of knowledge systems for problem solving using Case-Based Reasoning (CBR) technology. CBR is an intelligent systems methodology that enables information managers to increase efficiency and reduce cost by substantially automating processes (e.g., diagnosis, scheduling, or design). 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. Unfamiliar cases are solved and documented by retrieving and adapting solutions from similar stored cases. 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 this knowledge recycling can optimize resources spent on research and development. 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. 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. This paper discusses the application of the NaCoDAE Conversational CBR (CCBR) system for this process. NaCoDAE is a software package developed by at Naval Research Laboratory that 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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