Distributed and Parallel Databases
Taking the RDF Model Theory Out for a Spin
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
High performance reasoning with very large knowledge bases: a practical case study
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Time – space trade-offs in scaling up RDF schema reasoning
WISE'05 Proceedings of the 2005 international conference on Web Information Systems Engineering
The summary abox: cutting ontologies down to size
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Reducing the inferred type statements with individual grouping constructs
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
RDF packages: a scheme for efficient reasoning and querying over large-scale RDF data
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
The extension-based inference algorithm for pD*
Data & Knowledge Engineering
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In this paper, we propose a pragmatic approach where time consumption of RDFS reasoning remains fixed with increasing sizes of instance data. The approach infers facts about schema, but prevents producing facts about individuals. At the time of query answering the queries are rewritten. The query rewriting process does not result in complex or disjunctive queries due to the syntactic transformation that we made on the ontology and the rules. The most prominent contribution of this work is reducing reasoning to schema level without increasing query complexity. Thus, query execution performance improves in a considerable manner.