<div class="csl-bib-body">
<div class="csl-entry">Benedetto, D., Calautti, M., Hammad, H., Sallinger, E., & Vlad-Starrabba, A. (2025). A Datalog Rewriting Algorithm for Warded Ontologies. In <i>Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence</i> (pp. 4356–4364). https://doi.org/10.24963/ijcai.2025/485</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/221115
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dc.description.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.
en
dc.description.sponsorship
WWTF Wiener Wissenschafts-, Forschu und Technologiefonds
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dc.language.iso
en
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dc.subject
Knowledge Representation and Reasoning
en
dc.subject
Knowledge representation languages
en
dc.subject
Datalog
en
dc.subject
Algorithm
en
dc.subject
Ontology-Mediated Queries (OMQs)
en
dc.subject
Tuple-generating dependencies (TGDs)
en
dc.title
A Datalog Rewriting Algorithm for Warded Ontologies
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
University of Milan, Italy
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dc.contributor.affiliation
University of Trento, Italy
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dc.relation.isbn
978-1-956792-06-5
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dc.description.startpage
4356
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dc.description.endpage
4364
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dc.relation.grantno
VRG18-013
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
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tuw.peerreviewed
true
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tuw.project.title
Scalable Reasoning in Knowledge Graphs
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tuw.researchTopic.id
I1
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tuw.researchTopic.name
Logic and Computation
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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tuw.publication.orgunit
E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML)
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tuw.publisher.doi
10.24963/ijcai.2025/485
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dc.description.numberOfPages
9
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tuw.event.name
34th International Joint Conference on Artificial Intelligence (IJCAI)
en
tuw.event.startdate
16-08-2025
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tuw.event.enddate
22-08-2025
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Montreal
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tuw.event.country
CA
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tuw.event.presenter
Sallinger, Emanuel
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wb.sciencebranch
Informatik
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wb.sciencebranch
Mathematik
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
1010
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wb.sciencebranch.value
80
-
wb.sciencebranch.value
20
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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item.cerifentitytype
Publications
-
item.openairetype
conference paper
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item.fulltext
no Fulltext
-
item.languageiso639-1
en
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item.grantfulltext
none
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crisitem.author.dept
University of Milan, Italy
-
crisitem.author.dept
University of Trento, Italy
-
crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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crisitem.author.parentorg
E192 - Institut für Logic and Computation
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crisitem.project.funder
WWTF Wiener Wissenschafts-, Forschu und Technologiefonds