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

Author:

Hui Yang, Patrick Koopmann, Yue Ma, Nicole Bidoit

Keyword:

Computer Science, Artificial Intelligence, Artificial Intelligence (cs.AI), Logic in Computer Science (cs.LO)

journal:

date:

2023-05-15 16:00:00

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.

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