Efficient Computation of General Modules for ALC Ontologies (Extended Version)

TL;DR

This paper introduces a novel method for efficiently computing general modules in ALC ontologies, enabling more concise ontology representations that preserve entailments for specific terms, with improved size and computation time.

Contribution

It presents the first approach for general modules in ALC, leveraging uniform interpolation and new theoretical insights to enhance module size and computation efficiency.

Findings

General modules are often smaller than classical modules.

Our method computes modules faster than existing uniform interpolants.

The approach improves uniform interpolant and classical module computations.

Abstract

We present a method for extracting general modules for ontologies formulated in the description logic ALC. A module for an ontology is an ideally substantially smaller ontology that preserves all entailments for a user-specified set of terms. As such, it has applications such as ontology reuse and ontology analysis. Different from classical modules, general modules may use axioms not explicitly present in the input ontology, which allows for additional conciseness. So far, general modules have only been investigated for lightweight description logics. We present the first work that considers the more expressive description logic ALC. In particular, our contribution is a new method based on uniform interpolation supported by some new theoretical results. Our evaluation indicates that our general modules are often smaller than classical modules and uniform interpolants computed by the state-of-the-art, and compared with uniform interpolants, can be computed in a significantly shorter time. Moreover, our method can be used for, and in fact improves, the computation of uniform interpolants and classical modules.