Algorithm for Adapting Cases Represented in a Tractable Description Logic
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Case-based reasoning (CBR) based on description logics (DLs) has gained a lot of attention lately. Adaptation is a basic task in the CBR inference that can be modeled as the knowledge base revision problem and solved in propositional logic. However, in DLs, it is still a challenge problem since existing revision operators only work well for strictly restricted DLs of the DL-Lite family, and it is difficult to design a revision algorithm which is syntax-independent and fine-grained. In this paper, we present a new method for adaptation based on the DL EL_. Following the idea of adaptation as revision, we firstly extend the logical basis for describing cases from propositional logic to the DL EL_, and present a formalism for adaptation based on EL_. Then we present an adaptation algorithm for this formalism and demonstrate that our algorithm is syntax-independent and fine-grained. Our work provides a logical basis for adaptation in CBR systems where cases and domain knowledge are described by the tractable DL EL_.
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