Incremental Reasoning on Streams and Rich Background Knowledge

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BARBIERI, Davide Francesco, Daniele BRAGA, Stefano CERI, Emanuele DELLA VALLE, Michael GROSSNIKLAUS, 2010. Incremental Reasoning on Streams and Rich Background Knowledge. In: AROYO, Lora, ed., Grigoris ANTONIOU, ed., Eero HYVÖNEN, ed., Annette TEN TEIJE, ed., Heiner STUCKENSCHMIDT, ed., Liliana CABRAL, ed., Tania TUDORACHE, ed.. The Semantic Web: Research and Applications. Berlin, Heidelberg:Springer Berlin Heidelberg, pp. 1-15. ISBN 978-3-642-13485-2

@inproceedings{Barbieri2010Incre-25310, title={Incremental Reasoning on Streams and Rich Background Knowledge}, year={2010}, doi={10.1007/978-3-642-13486-9_1}, number={6088}, isbn={978-3-642-13485-2}, address={Berlin, Heidelberg}, publisher={Springer Berlin Heidelberg}, series={Lecture Notes in Computer Science}, booktitle={The Semantic Web: Research and Applications}, pages={1--15}, editor={Aroyo, Lora and Antoniou, Grigoris and Hyvönen, Eero and ten Teije, Annette and Stuckenschmidt, Heiner and Cabral, Liliana and Tudorache, Tania}, author={Barbieri, Davide Francesco and Braga, Daniele and Ceri, Stefano and Della Valle, Emanuele and Grossniklaus, Michael} }

Grossniklaus, Michael Della Valle, Emanuele Grossniklaus, Michael The semantic web: research and applications : 7th Extended Semantic Web Conference, ESWC 2010, Heraklion, Crete, Greece, May 30 - June 3, 2010, Proceedings, Part I / Lora Aroyo ... (eds.). - Berlin [u.a.] : Springer, 2010. - S. 1-15. - (Lecture notes in computer science ; 6088). - ISBN 978-3-642-13485-2 2013-12-05T07:33:53Z 2010 Incremental Reasoning on Streams and Rich Background Knowledge Braga, Daniele deposit-license Barbieri, Davide Francesco 2013-12-05T07:33:53Z This article presents a technique for Stream Reasoning, consisting in incremental maintenance of materializations of ontological entailments in the presence of streaming information. Previous work, delivered in the context of deductive databases, describes the use of logic programming for the incremental maintenance of such entailments. Our contribution is a new technique that exploits the nature of streaming data in order to efficiently maintain materialized views of RDF triples, which can be used by a reasoner.<br /><br />By adding expiration time information to each RDF triple, we show that it is possible to compute a new complete and correct materialization whenever a new window of streaming data arrives, by dropping explicit statements and entailments that are no longer valid, and then computing when the RDF triples inserted within the window will expire. We provide experimental evidence that our approach significantly reduces the time required to compute a new materialization at each window change, and opens up for several further optimizations. Barbieri, Davide Francesco Braga, Daniele Ceri, Stefano eng Della Valle, Emanuele Ceri, Stefano

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