Description Logics with Approximate Definitions - Precise Modeling of Vague Concepts

Abstract

We extend traditional Description Logics (DL) with a simple mechanism to handle approximate concept definitions in a qualitative way. Often, for example in medical applications, concepts are not definable in a crisp way but can fairly exhaustively be constrained through a particular sub- and a particular super-concept. We introduce such lower and upper approximations based on rough-set semantics, and show that reasoning in these languages can be reduced to standard DL satisfiability. This allows us to apply Rough Description Logics in a study of medical trials about sepsis patients, which is a typical application for precise modeling of vague knowledge. The study shows that Rough DL-based reasoning can be done in a realistic use case and that modeling vague knowledge helps to answer important questions in the design of clinical trials.