Computing Optimal Repairs of Quantified ABoxes w.r.t. Static ℰℒ TBoxes
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
The application of automated reasoning approaches to Description Logic (DL) ontologies may produce certain consequences that either are deemed to be wrong or should be hidden for privacy reasons. The question is then how to repair the ontology such that the unwanted consequences can no longer be deduced. An optimal repair is one where the least amount of other consequences is removed. Most of the previous approaches to ontology repair are of a syntactic nature in that they remove or weaken the axioms explicitly present in the ontology, and thus cannot achieve semantic optimality. In previous work, we have addressed the problem of computing optimal repairs of (quantified) ABoxes, where the unwanted consequences are described by concept assertions of the light-weight DL 𝓔𝓛. In the present paper, we improve on the results achieved so far in two ways. First, we allow for the presence of terminological knowledge in the form of an 𝓔𝓛 TBox. This TBox is assumed to be static in the sense that it cannot be changed in the repair process. Second, the construction of optimal repairs described in our previous work is best case exponential. We introduce an optimized construction that is exponential only in the worst case. First experimental results indicate that this reduces the size of the computed optimal repairs considerably.
Details
Original language | English |
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Title of host publication | Automated Deduction – CADE 28 - 28th International Conference on Automated Deduction, 2021, Proceedings |
Editors | André Platzer, Geoff Sutcliffe |
Publisher | Springer, Berlin [u. a.] |
Pages | 309-326 |
Number of pages | 18 |
Publication status | Published - 11 Jul 2021 |
Peer-reviewed | Yes |
Publication series
Series | Lecture Notes in Computer Science, Volume 12699 |
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ISSN | 0302-9743 |
Conference
Title | International Conference on Automated Deduction |
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Abbreviated title | CADE-28 |
Conference number | 28 |
Duration | 11 - 16 July 2021 |
Degree of recognition | International event |
Location | |
City | Virtual Event |
Country | United States of America |
External IDs
ORCID | /0000-0002-4049-221X/work/142247853 |
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ORCID | /0000-0002-9047-7624/work/142251237 |
ORCID | /0000-0003-0219-0330/work/153109366 |
Scopus | 85112327824 |
Keywords
ASJC Scopus subject areas
Keywords
- Compliance, Description logic, Privacy-preserving ontology publishing, Safety