Evaluation of knowledge acquisition (KA) is difficult in general. In recent times, incremental knowledge acquisition that emphasises direct communication between human experts and systems has been increasingly widely used. However, evaluating incremental KA techniques, like KA in general, has been difficult because of the costs of using human expertise in experimental studies. In this paper, we use a general simulation framework to evaluate Ripple Down Rules (RDR), a successful incremental KA method. We focus on two fundamental aspects of incremental KA: the importance of acquiring domain ontological structures and the usage of cornerstone cases. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Compton, P., & Cao, T. M. (2006). Evaluation of incremental knowledge acquisition with simulated experts. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4304 LNAI, pp. 39–48). Springer Verlag. https://doi.org/10.1007/11941439_8
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