Reasoning by Analogy in Description Logics Through Instance-based Learning

This work presents a method founded in instancebased learning for inductive (memory-based) reasoning on ABoxes. The method, which exploits a semantic dissimilarity measure between concepts and instances, can be employed both to answer class membership queries and to predict new assertions that may be not logically entailed by the knowledge base. In a preliminary experimentation, we show that the method is sound and it is actually able to induce new assertions that might be acquired in the knowledge base.