Remembering Why to Remember: Performance-Guided Case-Base Maintenance
(pdf
)
David B. Leake and David C. Wilson.
Advances in Case-Based Reasoning: Proceedings of EWCBR-2K.
13 pages. In press.
Abstract
An important focus of recent CBR research is on how to develop
strategies for achieving compact, competent case-bases, as a way to
improve the performance of CBR systems. However, compactness and
competence are not always good predictors of performance, especially
when problem distributions are non-uniform. Consequently, this paper
argues for developing methods that tie case-base maintenance more
directly to performance concerns. The paper begins by examining the
relationship between competence and performance, discussing the goals
and constraints that should guide addition and deletion of cases. It
next illustrates the importance of augmenting competence-based
criteria with quantitative performance-based considerations, and
proposes a strategy for closely reflecting adaptation performance
effects when compressing a case-base. It then presents empirical
studies examining the performance tradeoffs of current methods and the
benefits of applying fine-grained performance-based criteria to
case-base compression, showing that performance-based methods may be
especially important for task domains with non-uniform problem
distributions.
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