AILOAug 11, 2025

Fitting Description Logic Ontologies to ABox and Query Examples

arXiv:2508.08007v21 citationsh-index: 7DL
Originality Incremental advance
AI Analysis

This work addresses a foundational problem in ontology-mediated querying for knowledge representation and reasoning, with incremental contributions in complexity analysis.

The paper tackles the problem of fitting description logic ontologies to ABox and query examples, aiming to find an ontology that satisfies all positive examples and none of the negative ones. It provides effective characterizations and determines computational complexities, such as CO-NP for atomic queries and 2EXPTIME-complete for conjunctive queries.

We study a fitting problem inspired by ontology-mediated querying: given a collection of positive and negative examples of the form $(\mathcal{A},q)$ with $\mathcal{A}$ an ABox and $q$ a Boolean query, we seek an ontology $\mathcal{O}$ that satisfies $\mathcal{A} \cup \mathcal{O} \vDash q$ for all positive examples and $\mathcal{A} \cup \mathcal{O}\not\vDash q$ for all negative examples. We consider the description logics $\mathcal{ALC}$ and $\mathcal{ALCI}$ as ontology languages and a range of query languages that includes atomic queries (AQs), conjunctive queries (CQs), and unions thereof (UCQs). For all of the resulting fitting problems, we provide effective characterizations and determine the computational complexity of deciding whether a fitting ontology exists. This problem turns out to be ${\scriptsize CO}NP$ for AQs and full CQs and $2E{\scriptsize XP}T{\scriptsize IME}$-complete for CQs and UCQs. These results hold for both $\mathcal{ALC}$ and $\mathcal{ALCI}$.

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