Measuring similarity of individuals in description logics over the refinement space of conjunctive queries

Abstract

Similarity assessment is a key operation in several areas of artificial intelligence. This paper focuses on measuring similarity in the context of Description Logics (DL), and specifically on similarity between individuals. The main contribution of this paper is a novel approach based on measuring similarity in the space of Conjunctive Queries, rather than in the space of concepts. The advantage of this approach is two fold. On the one hand, it is independent of the underlying DL and therefore there is no need to design similarity measures for different DL, and, on the other hand, the approach is computationally more efficient than searching in the space of concepts.