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IEEE Transactions on Knowledge and Data Engineering
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Proceedings of the VLDB Endowment
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Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
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ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Query optimization for ontology-based information integration
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WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
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ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
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Proceedings of the 15th International Conference on Extending Database Technology
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ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
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In order to effectively and quickly answer queries in environments with distributed RDF/OWL, we present a query optimization algorithm to identify the potentially relevant Semantic Web data sources using structural query features and a term index. This algorithm is based on the observation that the join selectivity of a pair of query triple patterns is often higher than the overall selectivity of these two patterns treated independently. Given a rule goal tree that expresses the reformulation of a conjunctive query, our algorithm uses a bottom-up approach to estimate the selectivity of each node. It then prioritizes loading of selective nodes and uses the information from these sources to further constrain other nodes. Finally, we use an OWL reasoner to answer queries over the selected sources and their corresponding ontologies. We have evaluated our system using both a synthetic data set and a subset of the real-world Billion Triple Challenge data.