Susan Craw, Stewart Massie, Nirmalie Wiratunga
Knowledge maintenance for Case-Based Reasoning systems is an important knowledge engineering task despite the availability of initial case knowledge and new cases to extend it. For classification systems it is essential that different scenarios for the various classes are well represented and decision boundaries are well defined in the case knowledge. A complexity-based competence metric is proposed that identifies redundant and error-causing cases to be deleted. The metric informs a maintenance tool that enables the engineer to experiment and balance conflicting objectives. Complexity-informed maintenance outperforms benchmark algorithms for redundancy and error reduction tasks.
Subjects: 3.1 Case-Based Reasoning; 10. Knowledge Acquisition
Submitted: Apr 12, 2007