An Approach to Probabilistic Data Integration for the Semantic Web

Authors:
Andrea Calì;Thomas Lukasiewicz
Affiliations:
Oxford-Man Institute of Quantitative Finance, University of Oxford, Oxford, UK OX1 4EH and Computing Laboratory, University of Oxford, Oxford, UK OX1 3QD;Computing Laboratory, University of Oxford, Oxford, UK OX1 3QD
Venue:
Uncertainty Reasoning for the Semantic Web I
Year:
2008

Citing 16
Cited 0

The independent choice logic for modelling multiple agents under uncertainty

Artificial Intelligence - Special issue on economic principles of multi-agent systems
Navigational plans for data integration

AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Data integration: a theoretical perspective

Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database 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
Bayesian semantics for the semantic web

Bayesian semantics for the semantic web
Management of probabilistic data: foundations and challenges

Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Probabilistic description logic programs

International Journal of Approximate Reasoning
Expressive probabilistic description logics

Artificial Intelligence
Combining answer set programming with description logics for the Semantic Web

Artificial Intelligence
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
Tractable Probabilistic Description Logic Programs

SUM '07 Proceedings of the 1st international conference on Scalable Uncertainty Management
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)
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

Quantified Score

Hi-index	0.01

Visualization

Abstract

Probabilistic description logic programs are a powerful tool for knowledge representation in the Semantic Web, which combine description logics, normal programs under the answer set or well-founded semantics, and probabilistic uncertainty. The task of data integration amounts to providing the user with access to a set of heterogeneous data sources in the same fashion as when querying a single database, that is, through a global schema, which is a common representation of all the underlying data sources. In this paper, we make use of probabilistic description logic programs to model expressive data integration systems for the Semantic Web, where constraints are expressed both over the data sources and the global schema. We describe different types of probabilistic data integration, which aim especially at applications in the Semantic Web.