Efficient Axiomatization of OWL 2 EL Ontologies from Data by means of Formal Concept Analysis
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
We present an FCA-based axiomatization method that produces a complete 𝓔𝓛 TBox (the terminological part of an OWL 2 EL ontology) from a graph dataset in at most exponential time. We describe technical details that allow for efficient implementation as well as variations that dispense with the computation of extremely large axioms, thereby rendering the approach applicable albeit some completeness is lost. Moreover, we evaluate the prototype on real-world datasets.
Details
Originalsprache | Englisch |
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Titel | Proceedings of the 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024), February 20--27, 2024, Vancouver, Canada |
Redakteure/-innen | Michael Wooldridge, Jennifer Dy, Sriraam Natarajan |
Seiten | 10597-10606 |
Seitenumfang | 10 |
Band | 38 |
Auflage | 9 |
Publikationsstatus | Veröffentlicht - 25 März 2024 |
Peer-Review-Status | Ja |
Externe IDs
Scopus | 85189362462 |
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ORCID | /0000-0003-0219-0330/work/159607636 |