A logical notion of conditional independence: properties and applications
Artificial Intelligence - Special issue on relevance
Speeding up inferences using relevance reasoning: a formalism and algorithms
Artificial Intelligence - Special issue on relevance
Conditional independence in propositional logic
Artificial Intelligence
Deriving Inference Rules for Terminological Logics
JELIA '92 Proceedings of the European Workshop on Logics in AI
TABLEAUX '98 Proceedings of the International Conference on Automated Reasoning with Analytic Tableaux and Related Methods
Deriving Inference Rules for Description Logics: a Rewriting Approach into Sequent Calculi
Deriving Inference Rules for Description Logics: a Rewriting Approach into Sequent Calculi
Propositional independence: formula-variable independence and forgetting
Journal of Artificial Intelligence Research
Explaining subsumption in description logics
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Partition-based logical reasoning for first-order and propositional theories
Artificial Intelligence - Special volume on reformulation
Reducing OWL entailment to description logic satisfiability
Web Semantics: Science, Services and Agents on the World Wide Web
A Requirements Driven Framework for Benchmarking Semantic Web Knowledge Base Systems
IEEE Transactions on Knowledge and Data Engineering
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In this paper, we investigate the (in)dependence among OWL documents with respect to the logical consequence when they are combined, in particular the inference of concept and role assertions about individuals. On the one hand, we present a systematic approach to identifying those documents that affect the inference of a given fact. On the other hand, we consider ways for fast detection of independence. First, we demonstrate several special cases in which two documents are independent of each other. Secondly, we introduce an algorithm for checking the independence in the general case. In addition, we describe two applications in which the above results have allowed us to develop novel approaches to overcome some difficulties in reasoning with large scale OWL data. Both applications demonstrate the usefulness of this work for improving the scalability of a practical Semantic Web system that relies on the reasoning about individuals.