Formal concept analysis for knowledge refinement in case based reasoning

Abstract

Case-based Reasoning (CBR) is a problem solving paradigm that uses past experiences to solve new problems. Although CBR is supposed to alleviate the problem of knowledge acquisition, knowledge is still required to obtain the initial case base and to develop the processes of retrieving, reusing, revising and retaining cases. In this paper we propose the use of Formal Concept Analysis (FCA) to acquire and refine the knowledge available in a CBR system. In particular, we show how FCA can help to acquire indexing knowledge that supports the retrieval process, and also the use of FCA to improve the quality of the case base by identifying lack of coverage and biased combinations of case attributes.