Abstract
Case-based reasoning (CBR) based on description logics (DLs) has gained a lot of attention lately. Adaptation is a basic task in CBR that can be modeled as a knowledge base revision problem which has been solved in propositional logic. However, in DLs, adaptation is still a challenge problem since existing revision operators only work well for DLs of the DL-Lite family. It is difficult to design revision algorithms that are syntax-independent and fine-grained. In this paper, we propose a new method for adaptation based on the tractable DL \(\mathcal{EL_{\bot}}\). Following the idea of adaptation as revision, we firstly extend the logical basis for describing cases from propositional logic to DL and present a formalism for adaptation based on \(\mathcal{EL_{\bot}}\). Then we show that existing revision operators and algorithms in DLs can not be used for this formalism. Finally we present our adaptation algorithm. Our algorithm is syntax-independent and fine-grained, and satisfies the requirements on revision operators.
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Chang, L., Sattler, U., Gu, T. (2014). Algorithm for Adapting Cases Represented in a Tractable Description Logic. In: Lamontagne, L., Plaza, E. (eds) Case-Based Reasoning Research and Development. ICCBR 2014. Lecture Notes in Computer Science(), vol 8765. Springer, Cham. https://doi.org/10.1007/978-3-319-11209-1_6
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DOI: https://doi.org/10.1007/978-3-319-11209-1_6
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