  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 \emph{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 $\mathcal{EL_{\bot}}$. Following the idea of
adaptation as revision, we firstly extend the logical basis for describing
cases from propositional logic to the DL $\mathcal{EL_{\bot}}$, and present a
formalism for adaptation based on $\mathcal{EL_{\bot}}$. 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 $\mathcal{EL_{\bot}}$.
