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Adaptation knowledge acquisition in a CBR system

Abstract : In a case-based reasoning system, adaptation is a complicated task since it requires domain-specific knowledge, which is generally difficult to define. To acquire such knowledge, we propose a semi-automatic approach based on Formal Concept Analysis (FCA) techniques. We use Logical Concept Analysis (LCA), a generalization of FCA, to extract adaptation conditions that enhance the retrieval and adaptation processes. In this paper, we present this approach, that has been implemented in COBRA, our ontology-based CBR platform, and applied to the diagnosis of gas sensor failures.
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Submitted on : Friday, March 21, 2014 - 2:31:49 PM
Last modification on : Tuesday, November 16, 2021 - 4:30:26 AM

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Amjad Abou Assali, Dominique Lenne, Bruno Debray. Adaptation knowledge acquisition in a CBR system. International Journal on Artificial Intelligence Tools, World Scientific Publishing, 2013, 22 (1), pp.1250041. ⟨10.1142/S0218213012500418⟩. ⟨ineris-00963446⟩

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