Logical foundations of object-oriented and frame-based languages
Journal of the ACM (JACM)
Approximating Terminological Queries
FQAS '02 Proceedings of the 5th International Conference on Flexible Query Answering Systems
Description logic programs: combining logic programs with description logic
WWW '03 Proceedings of the 12th international conference on World Wide Web
How to reason with OWL in a logic programming system
RULEML '06 Proceedings of the Second International Conference on Rules and Rule Markup Languages for the Semantic Web
Unifying Reasoning and Search to Web Scale
IEEE Internet Computing
ELP: Tractable Rules for OWL 2
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Approximating OWL-DL ontologies
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Partial matchmaking using approximate subsumption
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Data complexity of reasoning in very expressive description logics
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Efficient OWL reasoning with logic programs: evaluations
RR'07 Proceedings of the 1st international conference on Web reasoning and rule systems
Resolution-Based approximate reasoning for OWL DL
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
A comparison of reasoning techniques for querying large description logic ABoxes
LPAR'06 Proceedings of the 13th international conference on Logic for Programming, Artificial Intelligence, and Reasoning
Scalable instance retrieval for the semantic web by approximation
WISE'05 Proceedings of the 2005 international conference on Web Information Systems Engineering
Approximating description logic classification for semantic web reasoning
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
What Is Approximate Reasoning?
RR '08 Proceedings of the 2nd International Conference on Web Reasoning and Rule Systems
ReduCE: A Reduced Coulomb Energy Network Method for Approximate Classification
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
GeoS '09 Proceedings of the 3rd International Conference on GeoSpatial Semantics
Approximate instance retrieval on ontologies
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I
Expressive approximations in DL-lite ontologies
AIMSA'10 Proceedings of the 14th international conference on Artificial intelligence: methodology, systems, and applications
Description logic TBoxes: model-theoretic characterizations and rewritability
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Towards ABox Modularization of semi-expressive Description Logics
Applied Ontology - Modularity in Ontologies
Towards efficient and practical solutions for ontology-based data management
Proceedings of the Joint EDBT/ICDT 2013 Workshops
Making the most of your triple store: query answering in OWL 2 using an RL reasoner
Proceedings of the 22nd international conference on World Wide Web
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With the increasing interest in expressive ontologies for the Semantic Web, it is critical to develop scalable and efficient ontology reasoning techniques that can properly cope with very high data volumes. For certain application domains, approximate reasoning solutions, which trade soundness or completeness for inctreased reasoning speed, will help to deal with the high computational complexities which state of the art ontology reasoning tools have to face. In this paper, we present a comprehensive overview of the Screech approach to approximate reasoning with OWL ontologies, which is based on the KAON2 algorithms, facilitating a compilation of OWL DL TBoxes into Datalog, which is tractable in terms of data complexity. We present three different instantiations of the Screech approach, and report on experiments which show that the gain in efficiency outweighs the number of introduced mistakes in the reasoning process.