Knowledge compilation and theory approximation
Journal of the ACM (JACM)
First-order logic and automated theorem proving (2nd ed.)
First-order logic and automated theorem proving (2nd ed.)
Reasoning in Description Logics by a Reduction to Disjunctive Datalog
Journal of Automated Reasoning
Computing minimum cost diagnoses to repair populated DL-based ontologies
Proceedings of the 17th international conference on World Wide Web
QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Approximating OWL-DL ontologies
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Supporting manual mapping revision using logical reasoning
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Inconsistency management and prioritized syntax-based entailment
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Reasoning with inconsistent ontologies
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
A Decomposition-Based Approach to Optimizing Conjunctive Query Answering in OWL DL
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Goal-Directed Module Extraction for Explaining OWL DL Entailments
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Extending description logics with uncertainty reasoning in possibilistic logic
International Journal of Intelligent Systems
Towards a complete OWL ontology benchmark
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Text2Onto: a framework for ontology learning and data-driven change discovery
NLDB'05 Proceedings of the 10th international conference on Natural Language Processing and Information Systems
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In order to directly reason over inconsistent OWL 2 DL ontologies, this paper considers linear order inference which comes from propositional logic. Consequences of this inference in an inconsistent ontology are defined as consequences in a certain consistent sub-ontology. This paper proposes a novel framework for compiling an OWL 2 DL ontology to a Horn propositional program so that the intended consistent sub-ontology for linear order inference can be approximated from the compiled result in polynomial time. A tractable method is proposed to realize this framework. It guarantees that the compiled result has a polynomial size. Experimental results show that the proposed method computes the exact intended sub-ontology for almost all test cases, while it is significantly more efficient and scalable than state-of-the-art exact methods.