Mary, What's Like All Cats?

In this extended abstract we report on results recently achieved for answering instance queries relaxed by concept similarity measures [4]. Traditionally, Description Logic (DL) reasoning systems only support crisp inference services, like subsumption and instances queries. The latter can be effectively used to perform different types of search tasks: Given an ABox describing a set of individuals, an instance query returns all those that are instance of the query concept Q, rejecting all others. However, often it is also interesting to consider those individuals that are not instances: Are they completely different to Q or how similar are they to Q? In cases where the original query does not retrieve any resulting individuals, those individuals that are ‘very close’ to being an instance can still be a good alternative. The instance queries that do not only return the instances but also those that nearly match the query concept are called relaxed instance queries [3]. A natural way to relax instance queries is by using concept similarity measures (CSMs). Such a measure ∼ is a function that assigns to each pair of concepts a similarity value between 0 and 1. Together with a fixed threshold t, the instance query can be relaxed by returning all individuals that are instance of a concept with a similarity value of at least t to the query concept w.r.t. ∼. One advantage of using CSMs as a parameter for this inference is that they can implement different notions of similarity, and regard certain features more important than others. This allows to relax queries with respect to certain features, but leave others fixed (compare Figure 1).