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 FC A 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. © 2006 Springer-Verlag London.
CITATION STYLE
Díaz-Agudo, B., Gómez-Martín, M. A., Gómez-Martín, P. P., & González-Calero, P. A. (2006). Formal concept analysis for knowledge refinement in case based reasoning. In Research and Development in Intelligent Systems XXII - Proceedings of AI 2005, the 25th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence (pp. 233–245). Springer London. https://doi.org/10.1007/978-1-84628-226-3_18
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