A Taxonomy of Similarity Mechanisms for Case-Based Reasoning

Assessing the similarity between cases is a key aspect of the retrieval phase in case-based reasoning (CBR). In most CBR work, similarity is assessed based on feature-value descriptions of cases using similarity metrics which use these feature values. In fact it might be said that this notion of a feature-value representation is a defining part of the CBR world-view – it underpins the idea of a problem space with cases located relative to each other in this space. Recently a variety of similarity mechanisms have emerged that are not founded on this feature-space idea. Some of these new similarity mechanisms have emerged in CBR research and some have arisen in other areas of data analysis. In fact research on Support Vector Machines (SVM) is a rich source of novel similarity representations because of the emphasis on encoding domain knowledge in the kernel function of the SVM. In this paper we present a taxonomy that organises these new similarity mechanisms and more established similarity mechanisms in a coherent framework.