The independent choice logic for modelling multiple agents under uncertainty
Artificial Intelligence - Special issue on economic principles of multi-agent systems
P-SHOQ(D): A Probabilistic Extension of SHOQ(D) for Probabilistic Ontologies in the Semantic Web
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
A Probabilistic XML Approach to Data Integration
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Probabilistic description logic programs
International Journal of Approximate Reasoning
A Novel Combination of Answer Set Programming with Description Logics for the Semantic Web
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
PR-OWL: A Framework for Probabilistic Ontologies
Proceedings of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006)
Reducing OWL entailment to description logic satisfiability
Web Semantics: Science, Services and Agents on the World Wide Web
Tightly integrated probabilistic description logic programs for the semantic web
ICLP'07 Proceedings of the 23rd international conference on Logic programming
A bayesian network approach to ontology mapping
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Probabilistic ontologies and relational databases
OTM'05 Proceedings of the 2005 Confederated international conference on On the Move to Meaningful Internet Systems - Volume >Part I
Expressive probabilistic description logics
Artificial Intelligence
Combining answer set programming with description logics for the Semantic Web
Artificial Intelligence
An Approach to Probabilistic Data Integration for the Semantic Web
Uncertainty Reasoning for the Semantic Web I
Tightly Coupled Probabilistic Description Logic Programs for the Semantic Web
Journal on Data Semantics XII
Uncertainty in the Semantic Web
SUM '09 Proceedings of the 3rd International Conference on Scalable Uncertainty Management
Uncertainty Reasoning for the Semantic Web
RR '09 Proceedings of the 3rd International Conference on Web Reasoning and Rule Systems
Tightly integrated probabilistic description logic programs for representing ontology mappings
Annals of Mathematics and Artificial Intelligence
| Hi-index | 0.00 |
We propose tractable probabilistic description logic programs (or probabilistic dl-programs) for the Semantic Web, which combine tractable description logics, normal programs under the answer set semantics, and probabilities. In particular, we introduce the total well-founded semanticsfor probabilistic dl-programs. Contrary to the previous answer set and well-founded semantics, it is defined for all probabilistic dl-programs and all probabilistic queries. Furthermore, tight (resp., tight literal) query processing under the total well-founded semantics coincides with tight (resp., tight literal) query processing under the previous well-founded (resp., answer set) semantics whenever the latter is defined. We then present an anytime algorithm for tight query processing in probabilistic dl-programs under the total well-founded semantics. We also show that tight literal query processing in probabilistic dl-programs under the total well-founded semantics can be done in polynomial time in the data complexity and is complete for EXP in the combined complexity. Finally, we describe an application of probabilistic dl-programs in probabilistic data integration for the Semantic Web.