Abstract
In most case-based reasoning (CBR) systems there has been little research done on validating new knowledge, specifically on how previous knowledge differs from current knowledge by means of conceptual change. This paper proposes a technique that enables the domain expert who is non-expert in artificial intelligence (AI) to interactively supervise the knowledge validation process in a CBR system. The technique is based on formal concept analysis which involves a graphical representation and comparison of the concepts, and a summary description highlighting the conceptual differences. We propose a dissimilarity metric for measuring the degree of variation between the previous and current concepts when a new case is added to the knowledge base. The developed technique has been evaluated by a dermatology consultant, and has shown to be useful for discovering ambiguous cases and keeping the database consistent.
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Ou, M.H., West, G.A.W., Lazarescu, M., Clay, C. (2005). Interactive Knowledge Validation in CBR for Decision Support in Medicine. In: Miksch, S., Hunter, J., Keravnou, E.T. (eds) Artificial Intelligence in Medicine. AIME 2005. Lecture Notes in Computer Science(), vol 3581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527770_41
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DOI: https://doi.org/10.1007/11527770_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27831-3
Online ISBN: 978-3-540-31884-2
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