Integrating Knowledge-Based and Case-Based Reasoning

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Date
2006-08-30Author
Chabuk, Timur
Seifter, Mark
Salasin, John
Reggia, James
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There has been substantial recent interest in integrating knowledge based
reasoning (KBR) and case-based reasoning (CBR) within a single system due
to the potential synergisms that could result. Here we describe our recent
work investigating the feasibility of a combined KBR-CBR
application-independent system for interpreting multi-episode
stories/narratives, illustrating it with an application in the domain of
interpreting urban warfare stories. A genetic algorithm is used to derive
weights for selection of the most relevant past cases. In this setting,
we examine the relative value of using input features of a problem for
case selection versus using features inferred via KBR, versus both. We
find that using both types of features is best (compared to human
selection), but that input features are most helpful and inferred features
are of marginal value. This finding supports the idea that KBR and CBR
provide complimentary rather than redundant information, and hence that
their combination in a single system is likely to be useful.