|
|
|
Lightweight axiom pinpointing via replicated driver and customized SAT-solving |
Dantong OUYANG1,2, Mengting LIAO1, Yuxin YE1,2( ) |
1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
2. Key Laboratory of Symbolic Computation and Knowledge Engineering (Jilin University), Ministry of Education, Changchun 130012, China |
|
|
|
|
Abstract In description logic, axiom pinpointing is used to explore defects in ontologies and identify hidden justifications for a logical consequence. In recent years, SAT-based axiom pinpointing techniques, which rely on the enumeration of minimal unsatisfiable subsets (MUSes) of pinpointing formulas, have gained increasing attention. Compared with traditional Tableau-based reasoning approaches, SAT-based techniques are more competitive when computing justifications for consequences in large-scale lightweight description logic ontologies. In this article, we propose a novel enumeration justification algorithm, working with a replicated driver. The replicated driver discovers new justifications from the explored justifications through cheap literals resolution, which avoids frequent calls of SAT solver. Moreover, when the use of SAT solver is inevitable, we adjust the strategies and heuristic parameters of the built-in SAT solver of axiom pinpointing algorithm. The adjusted SAT solver is able to improve the checking efficiency of unexplored sub-formulas. Our proposed method is implemented as a tool named RDMinA. The experimental results show that RDMinA outperforms the existing axiom pinpointing tools on practical biomedical ontologies such as Gene, Galen, NCI and Snomed-CT.
|
| Keywords
axiom pinpointing
description logic
SAT solver
|
|
Corresponding Author(s):
Yuxin YE
|
|
Just Accepted Date: 31 December 2021
Issue Date: 02 August 2022
|
|
| 1 |
F, Baader D, Calvanese D L, Mcguinness, et al.. The Description Logic Handbook. Cambridge University Press, 2007
|
| 2 |
F, Baader R, Peñaloza B Suntisrivaraporn. Pinpointing in the description logic EL+. In: Proceedings of the 30th Annual German Conference on Artificial Intelligence. 2007, 52– 67
|
| 3 |
F, Baader B Suntisrivaraporn. Debugging snomed CT using axiom pinpointing in the description logic EL+. In: Proceedings of the 3rd International Conference on Knowledge Representation in Medicine. 2008, 1
|
| 4 |
B, Suntisrivaraporn F, Baader S, Schulz K Spackman. Replacing SEP-Triplets in SNOMED CT using tractable description logic operators. In: Proceedings of the 11th Conference on Artificial Intelligence in Medicine. 2007, 287– 291
|
| 5 |
F, Baader S, Brandt C Lutz. Pushing the EL envelope . In: Proceedings of the 19th International Joint Conference on Artificial Intelligence. 2005, 364– 369
|
| 6 |
R, Sebastiani M Vescovi. Axiom pinpointing in lightweight description logics via horn-sat encoding and conflict analysis. In: Proceedings of the 22nd International Conference on Automated Deduction. 2009, 84– 99
|
| 7 |
M F, Arif C, Mencía J Marques-Silva. Efficient axiom pinpointing with EL2MCS. In: Proceedings of the 38th Annual German Conference on Artificial Intelligence. 2015, 225– 233
|
| 8 |
M F, Arif C, Mencía J Marques-Silva. Efficient MUS enumeration of Horn formulae with applications to axiom pinpointing. In: Proceedings of the 18th International Conference on Theory and Applications of Satisfiability Testing. 2015, 324– 342
|
| 9 |
N, Manthey R, Peñaloza S Rudolph. Efficient axiom pinpointing in EL using SAT technology . In: Proceedings of the 29th International Workshop on Description Logics. 2016
|
| 10 |
M F, Arif C, Mencía A, Ignatiev N, Manthey R, Peñaloza J Marques-Silva. BEACON: an efficient SAT-based tool for debugging EL+ ontologies . In: Proceedings of the 19th International Conference on Theory and Applications of Satisfiability Testing. 2016, 521– 530
|
| 11 |
A, Ignatiev J, Marques-Silva C, Mencía R Peñaloza. Debugging EL+ ontologies through horn MUS enumeration . In: Proceedings of the 30th International Workshop on Description Logics. 2017, 1
|
| 12 |
Y, Kazakov P Skočovský. Enumerating justifications using resolution. In: Proceedings of the 9th International Joint Conference on Automated Reasoning. 2018, 609– 626
|
| 13 |
M, Gao Y, Ye D, Ouyang B Wang. Finding justifications by approximating core for large-scale ontologies. In: Proceedings of the 28th International Joint Conference on Artificial Intelligence. 2019, 6432– 6433
|
| 14 |
N, Manthey R, Peñaloza S Rudolph . SATPIN: Axiom pinpointing for lightweight description logics through incremental SAT. KI-Künstliche Intelligenz, 2020, 34( 3): 389– 394
|
| 15 |
Y, Ye X, Cui D Ouyang . Extracting a justification for OWL ontologies by critical axioms. Frontiers of Computer Science, 2020, 14( 4): 144305
|
| 16 |
J, Gao D T, Ouyang Y Ye . Exploring duality on ontology debugging. Applied Intelligence, 2020, 50( 2): 620– 633
|
| 17 |
N, Sörensson N Een. MiniSat v1.13- A SAT solver with conflict-clause minimization. In: Proceedings of the 8th Conference on Theory and Applications of Satisfiability Testing. 2005, 502– 518
|
| 18 |
M Minoux. LTUR: a simplified linear-time unit resolution algorithm for Horn formulae and computer implementation. Information Processing Letters, 1988, 29(1): 1– 12
|
| 19 |
F, Baader C, Lutz B Suntisrivaraporn. Efficient reasoning in EL+. In: Proceedings of the 2006 International Workshop on Description Logics. 2006, 15
|
| 20 |
J, Bailey P J Stuckey. Discovery of minimal unsatisfiable subsets of constraints using hitting set dualization. In: Proceedings of the 7th International Symposium on Practical Aspects of Declarative Languages. 2005, 174– 186
|
| 21 |
J, Bendík N, Benes I, Cerná J Barnat. Tunable online MUS/MSS enumeration. In: Proceedings of the 36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science. 2016, 50: 1– 50: 13
|
| 22 |
N, Narodytska N, Bjørner M C, Marinescu M Sagiv. Core-guided minimal correction set and core enumeration. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence. 2018, 1353– 1361
|
| 23 |
J, Bendík I, Černá N Beneš. Recursive online enumeration of all minimal unsatisfiable subsets. In: Proceedings of the 16th International Symposium on Automated Technology for Verification and Analysis. 2018, 143– 159
|
| 24 |
J, Bendík I Černá. Replication-guided enumeration of minimal unsatisfiable subsets. In: Proceedings of the 26th International Conference on Principles and Practice of Constraint Programming. 2020, 37– 54
|
| 25 |
J, Bendík I Černá. MUST: Minimal unsatisfiable subsets enumeration tool. In: Proceedings of the 26th International Conferences on Tools and Algorithms for the Construction and Analysis of Systems. 2020, 135– 152
|
| 26 |
R, Peñaloza B Sertkaya. On the complexity of axiom pinpointing in the EL family of description logics. In: Proceedings of the 12th International Conference on Principles of Knowledge Representation and Reasoning. 2010, 280– 289
|
| 27 |
J, Marques-Silva A, Ignatiev C, Mencía R Peñaloza. Efficient reasoning for inconsistent horn formulae. In: Proceedings of the 15th European Conference on Logics in Artificial Intelligence. 2016, 336– 352
|
| 28 |
A, Belov J Marques-Silva. MUSer2: an efficient MUS extractor. Journal on Satisfiability, Boolean Modeling and Computation, 2012, 8(3–4): 123– 128
|
| 29 |
F, Bacchus G Katsirelos. Using minimal correction sets to more efficiently compute minimal unsatisfiable sets. In: Proceedings of the 27th International Conference on Computer Aided Verification. 2015, 70– 86
|
| 30 |
P, Kilby J, Slaney S, Thiébaux T Walsh. Backbones and backdoors in satisfiability. In: Proceedings of the 20th National Conference on Artificial Intelligence. 2005, 1368– 1373
|
| 31 |
G, Audemard L Simon. Predicting learnt clauses quality in modern SAT solvers. In: Proceedings of the 21st International Joint Conference on Artificial Intelligence. 2009, 399– 404
|
| 32 |
M W, Moskewicz C F, Madigan Y, Zhao L, Zhang S Malik. Chaff: engineering an efficient SAT solver. In: Proceedings of the 38th Annual Design Automation Conference. 2001, 530– 535
|
| 33 |
J H, Liang V, Ganesh E, Zulkoski A, Zaman K Czarnecki. Understanding VSIDS branching heuristics in conflict-driven clause-learning SAT solvers. In: Proceedings of the 11th International Haifa Verification Conference on Hardware and Software: Verification and Testing. 2015, 225– 241
|
| 34 |
C Oh. Between SAT and UNSAT: the fundamental difference in CDCL SAT. In: Proceedings of the 18th International Conference on Theory and Applications of Satisfiability Testing. 2015, 307– 323
|
| 35 |
A, Morgado M, Liffiton J Marques-Silva. MaxSAT-based MCS enumeration. In: Proceedings of the 8th International Haifa Verification Conference on Hardware and Software: Verification and Testing. 2012, 86– 101
|
| 36 |
M H, Liffiton K A Sakallah. Algorithms for computing minimal unsatisfiable subsets of constraints. Journal of Automated Reasoning, 2008, 40(1): 1– 33
|
| 37 |
M H, Liffiton A, Previti A, Malik J Marques-Silva. Fast, flexible MUS enumeration. Constraints, 2016, 21(2): 223– 250
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
