Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/1003
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dc.contributor.authorSpasić, Mirkoen_US
dc.contributor.authorJovanovik, Milosen_US
dc.contributor.authorPrat-Pérez, Arnauen_US
dc.date.accessioned2022-08-17T11:19:52Z-
dc.date.available2022-08-17T11:19:52Z-
dc.date.issued2016-01-01-
dc.identifier.issn16130073en
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/1003-
dc.description.abstractSynthetic datasets used in benchmarking need to mimic all characteristics of real-world datasets, in order to provide realistic benchmarking results. Synthetic RDF datasets usually show a significant discrepancy in the level of structuredness compared to real-world RDF datasets. This structural difference is important as it directly affects storage, indexing and querying. In this paper, we show that the synthetic RDF dataset used in the Social Network Benchmark is characterized with high-structuredness and therefore introduce modifications to the data generator so that it produces an RDF dataset with a real-world structuredness.en
dc.relation.ispartofCEUR Workshop Proceedingsen_US
dc.subjectBenchmarksen
dc.subjectBig dataen
dc.subjectData generationen
dc.subjectLinked dataen
dc.subjectRDFen
dc.subjectSocial network benchmarken
dc.subjectSynthetic dataen
dc.titleAn RDF dataset generator for the social network benchmark with real-world coherenceen_US
dc.typeConference Paperen_US
dc.relation.publicationProceedings of the Workshop on Benchmarking Linked Data (BLINK 2016)en_US
dc.identifier.scopus2-s2.0-84992645497-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84992645497-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.relation.volume1700en_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairetypeConference Paper-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.orcid0000-0002-9304-4007-
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