Title: Approximate Representation and Reasoning in Description Logics
Project duration: Until end of September 2025
Research Area: Knowledge Representation and Engineering
A considerable amount of research has been devoted to extending traditional Description Logics (DLs) with non-classical semantics that can be used to represent, and reason about, imprecise or approximate knowledge. In this project, we extend previous work on approximation in DLs in two directions. The first focuses on approximate representation and reasoning for ontology-mediated query answering (OMQA). By using approximation, an OMQA system can provide answers that only approximately match the conditions stated in a query, but may nevertheless be of interest for the user. The second direction considers unification in DLs, which tries to make concepts equivalent by adding definitions for atomic concepts. This yields an approximation of equivalence of concepts, which can, e.g., be used to detect redundancies in ontologies.
In the project “Approximate Representation and Reasoning in Description Logics”, we have two main goals. The first consists of thoroughly comparing the approaches for approximately defining concepts and approximately answering queries, introduced in our previous work. Based on this, we aim to develop a comprehensive framework for OMQA under approximate semantics. Our second objective is to study the decidability and complexity of unification in lightweight DLs w.r.t. ontologies, and to develop practical algorithms for the decidable cases.
We compare the approaches from our previous work on approximation w.r.t. their expressive power and their computational complexity. Relevant questions in this context include: Is using one approach more efficient than using another? Compare precision and recall of different approaches? Regarding unification, existing techniques cannot deal with arbitrary ontologies, but only with ones satisfying a certain restriction on cyclic dependencies. The main problem is thus to develop new methods that can handle the general case.
This project requires deep knowledge of the investigated DLs. We also use techniques from complexity theory, logic in computer science, databases, unification theory and automata theory.
Our framework for approximately answering queries represents a first step towards extending OMQA systems with approximate semantics. We believe that such systems would enrich the user’s experience during query answering. In particular, approximate answers can be very useful in scenarios where a query has no (only a few) exact answers. Regarding unification, the decidability status of unification w.r.t. unrestricted ontologies in sub-Boolean DLs is a big open problem. A solution to this problem will also be of great interest to researchers on unification theory.