Existential rules, a.k.a. tuple-generating dependencies (TGDs), form a well-established formalism for specifying ontologies. In particular, the warded language is a well-behaved fragment of TGD-based ontologies, striking a good balance between expressive power and computational complexity of answering Ontology-Mediated Queries (OMQs). The theoretical foundations of answering OMQs over warded ontologies are by now well-understood, but to the best of our knowledge, very few efforts exist that exploit such a rich theory for building practical query answering algorithms. Our goal is to fill the above gap by designing a novel Datalog rewriting algorithm for OMQs over warded ontologies which is amenable to practical implementations, as well as providing an implementation and an experimental evaluation, with the aim of understanding how key input parameters affect the performance of this approach, and what are its limits when combined with off-the-shelf Datalog-based engines.

A Datalog Rewriting Algorithm for Warded Ontologies / D. Benedetto, M. Calautti, H. Hammad, E. Sallinger, A. Vlad-Starrabba - In: IJCAI International Joint Conference on Artificial Intelligence[s.l] : International Joint Conferences on Artificial Intelligence, 2025. - ISBN 9781956792065. - pp. 4356-4364 (( 34. Internationa Joint Conference on Artificial Intelligence : August , 16 - 22 Montreal (Canada) 2025 [10.24963/ijcai.2025/485].

A Datalog Rewriting Algorithm for Warded Ontologies

M. Calautti
Secondo
;
2025

Abstract

Existential rules, a.k.a. tuple-generating dependencies (TGDs), form a well-established formalism for specifying ontologies. In particular, the warded language is a well-behaved fragment of TGD-based ontologies, striking a good balance between expressive power and computational complexity of answering Ontology-Mediated Queries (OMQs). The theoretical foundations of answering OMQs over warded ontologies are by now well-understood, but to the best of our knowledge, very few efforts exist that exploit such a rich theory for building practical query answering algorithms. Our goal is to fill the above gap by designing a novel Datalog rewriting algorithm for OMQs over warded ontologies which is amenable to practical implementations, as well as providing an implementation and an experimental evaluation, with the aim of understanding how key input parameters affect the performance of this approach, and what are its limits when combined with off-the-shelf Datalog-based engines.
Knowledge Representation and Reasoning: KRR: Applications; Knowledge Representation and Reasoning: KRR: Knowledge representation languages;
Settore IINF-05/A - Sistemi di elaborazione delle informazioni
Settore INFO-01/A - Informatica
   Dynamic Disinformation Networks: Where is the Truth? (DISTORT)
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   MINISTERO DELL'UNIVERSITA' E DELLA RICERCA
   P2022KHTX7_003
2025
International Joint Conferences on Artifical Intelligence (IJCAI)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1229982
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