Attributive concept descriptions with complements
Artificial Intelligence
Handbook of logic in artificial intelligence and logic programming (vol. 3)
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Resource-Bounded Paraconsistent Inference
Annals of Mathematics and Artificial Intelligence
A Probabilistic Extension to Ontology Language OWL
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 4 - Volume 4
Debugging and repair of owl ontologies
Debugging and repair of owl ontologies
Extending Description Logics with Uncertainty Reasoning in Possibilistic Logic
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A Proposal to Handle Inconsistent Ontology with Fuzzy OWL
CSIE '09 Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering - Volume 01
Reasoning with inconsistent ontologies
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Reasoning with Inconsistent OWL Ontologies for Software Reuse
WCSE '09 Proceedings of the 2009 WRI World Congress on Software Engineering - Volume 02
P-CLASSIC: a tractable probablistic description logic
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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
Towards a fuzzy description logic for the semantic web (preliminary report)
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
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With the development of semantic web, the quality and correctness of ontologies play more and more important roles in semantic representation and knowledge sharing. However, ontologies are often inconsistent and uncertain in real situations. Because of the difficulty in ensuring the quality of ontologies, there is an increasing need for dealing with the inconsistency and uncertainty in real-world applications of ontological reasoning and management. This paper adopts two methods to handle the inconsistent and uncertain ontologies: the first one is to repair the inconsistency, algorithms RIO and RIUO are proposed to compute the candidate repair set, the consistency of ontology could be recovered through deleting or modifying the axioms in candidate repair set; the second one is to develop a non-standard reasoning method to obtain meaningful answers, algorithms RMU and RMIU are proposed to perform query-specific reasoning methods for inconsistent and uncertain ontologies without changing the original ontologies. Finally the prototype system is constructed and the experiment results validate the usability and effectiveness of our approaches.