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hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorFarvardin, Mohammad Amin
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorColazzo, Dario
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorBelhajjame, Khalid
dc.contributor.authorSartiani, Carlo
dc.date.accessioned2021-11-25T09:47:45Z
dc.date.available2021-11-25T09:47:45Z
dc.date.issued2020
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/22241
dc.language.isoenen
dc.subjectBig dataen
dc.subject.ddc005en
dc.titleScalable Saturation of Streaming RDF Triplesen
dc.typeChapitre d'ouvrage
dc.description.abstractenIn the Big Data era, RDF data are produced in high volumes. While there exist proposals for reasoning over large RDF graphs using big data platforms, there is a dearth of solutions that do so in environments where RDF data are dynamic, and where new instance and schema triples can arrive at any time. In this work, we present the first solution for reasoning over large streams of RDF data using big data platforms. In doing so, we focus on the saturation operation, which seeks to infer implicit RDF triples given RDF Schema or OWL constraints. Indeed, unlike existing solutions which saturate RDF data in bulk, our solution carefully identifies the fragment of the existing (and already saturated) RDF dataset that needs to be considered given the fresh RDF statements delivered by the stream. Thereby, it performs the saturation in an incremental manner. Experimental analysis shows that our solution outperforms existing bulk-based saturation solutions.en
dc.identifier.citationpages1-40en
dc.relation.ispartoftitleTransactions on Large-Scale Data- and Knowledge-Centered Systems XLIV : Special Issue on Data Management – Principles, Technologies, and Applicationsen
dc.relation.ispartofeditorHameurlain, Abdelkader
dc.relation.ispartofeditorTjoa, A Min
dc.relation.ispartofeditorLamarre, Philippe
dc.relation.ispartofeditorZeitouni, Karine
dc.relation.ispartofpublnameSpringeren
dc.relation.ispartofdate2020
dc.relation.ispartofpages195en
dc.relation.ispartofurl10.1007/978-3-662-62271-1en
dc.subject.ddclabelProgrammation, logiciels, organisation des donnéesen
dc.relation.ispartofisbn978-3-662-62270-4en
dc.relation.forthcomingnonen
dc.identifier.doi10.1007/978-3-662-62271-1_1en
dc.description.ssrncandidatenon
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2021-11-25T09:44:06Z
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