Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6028
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dc.contributor.authorÖzkan, E. C.-
dc.contributor.authorSaleem, M.-
dc.contributor.authorDoğdu, Erdoğan-
dc.contributor.authorNgomo, A. C. N.-
dc.date.accessioned2021-09-11T15:21:32Z-
dc.date.available2021-09-11T15:21:32Z-
dc.date.issued2016en_US
dc.identifier.citation3rd International Workshop on Dataset PROFIling and fEderated Search for Linked Data, PROFILES 2016, 30 May 2016, , 122216en_US
dc.identifier.issn1613-0073-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6028-
dc.description.abstractEfficient source selection is one of the most important optimization steps in federated SPARQL query processing as it leads to more efficient query execution plan generation. An over-estimation of the data sources will generate extra network traffic by retrieving irrelevant intermediate results. Such intermediate results will be excluded after performing joins between triple patterns. Consequently an over-estimation of sources may result in increased query execution time. Devising triple patterns join-aware source selection approaches has shown to yield great improvement potential. In this work, we present UPSP, a new source selection approach for SPARQL query federation over multiple SPARQL endpoints. UPSP makes use of the subject-subject, subject-object, object-subject, and object-object joins information stored in an index structure to perform efficient triple patterns join-aware source selection. Our evaluation results on FedBench shows that UPSP outperforms state-of-the-art source selection approaches by selecting smaller number of sources (without losing recall) and reducing the query execution times.en_US
dc.language.isoenen_US
dc.publisherCEUR-WSen_US
dc.relation.ispartofCEUR Workshop Proceedingsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFederated queryen_US
dc.subjectHibiscusen_US
dc.subjectLinked dataen_US
dc.subjectSource pruningen_US
dc.titleUPSP: Unique predicate-based source selection for SPARQL endpoint federationen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.volume1597en_US
dc.identifier.scopus2-s2.0-84977597915en_US
dc.institutionauthorDoğdu, Erdoğan-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conference3rd International Workshop on Dataset PROFIling and fEderated Search for Linked Data, PROFILES 2016en_US
dc.identifier.scopusquality--
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeConference Object-
item.cerifentitytypePublications-
item.languageiso639-1en-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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