Empirical evaluation of retrieval in case-based reasoning systems using modified cosine matching function

Case-based reasoning (CBR) supports ill-structured decision making by retrieving previous cases that are useful toward the solution of a new decision problem. The usefulness of previous cases is determined by assessing the similarity of a new case with the previous cases. In this paper, we present a modified form of the cosine matching function that makes it possible to contrast the two cases being matched and to include differences in the importance of features in the new case and the importance of features in the previous case. Our empirical evaluation of a CBR application to a diagnosis and repair task in an electromechanical domain shows that the proposed modified cosine matching function has a superior retrieval performance when compared to the performance of nearest-neighbor and the Tversky's contrast matching functions.