Efficient Axiomatization of OWL 2 EL Ontologies from Data by means of Formal Concept Analysis
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
Contributors
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
Original language | English |
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Title of host publication | Proceedings of the 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024), February 20--27, 2024, Vancouver, Canada |
Editors | Michael Wooldridge, Jennifer Dy, Sriraam Natarajan |
Pages | 10597-10606 |
Number of pages | 10 |
Volume | 38 |
Edition | 9 |
Publication status | Published - 25 Mar 2024 |
Peer-reviewed | Yes |
External IDs
Scopus | 85189362462 |
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ORCID | /0000-0003-0219-0330/work/159607636 |