D. Patterson, W. Dubitzky, S. S. Anand, and J. G. Hughes
Recent applications of Case-Based Reasoning (CBR) industry have highlighted two major difficulties with developing CBR systems. These are, the integration of types of knowledge which are orthogonal to the knowledge represented by cases and the case engineering bottleneck. Exploiting the affinity between Data Mining and CBR we propose a unifying framework addressing these issues. Emphasising the automation of the entire CBR process we outline the Data Mining paradigms that may be employed and present initial results.