- Titel
- Efficient Axiomatization of OWL 2 EL Ontologies from Data by means of Formal Concept Analysis
- Untertitel
- (Extended Version)
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-885706
- Schriftenreihe
- LTCS-Report
- Bandnummer
- 23-01
- Erstveröffentlichung
- 2023
- DOI
- https://doi.org/10.25368/2023.214
- Abstract (EN)
- 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.
- This is an extended version of an article accepted at AAAI 2024.
- Zitiert in
- Proceedings of the 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024)
- Freie Schlagwörter (DE)
- Beschreibungslogik, Formale Begriffsanalyse, Axiomatisierung, OWL 2 EL, Ontologie, TBox
- Freie Schlagwörter (EN)
- Description Logic, Formal Concept Analysis, Axiomatization, OWL 2 EL, Ontology, TBox
- Klassifikation (DDC)
- 004
- Klassifikation (RVK)
- ST 136
- Herausgeber (Institution)
- Technische Universität Dresden
- Förder- / Projektangaben
- Deutsche Forschungsgemeinschaft Repairing Description Logic Ontologies
ID: 430150274 - Deutsche Forschungsgemeinschaft TRR 248: Foundations of Perspicuous Software Systems - Enabling Comprehension in a Cyber-Physical World
ID: 389792660 - Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-885706
- Veröffentlichungsdatum Qucosa
- 28.12.2023
- Dokumenttyp
- Bericht
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY 4.0