Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/17645
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dc.contributor.authorJovanovik, Milosen_US
dc.contributor.authorSpasić, Mirkoen_US
dc.contributor.authorPrat-Pérez, Arnauen_US
dc.date.accessioned2022-05-18T07:22:24Z-
dc.date.available2022-05-18T07:22:24Z-
dc.date.issued2016-10-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/17645-
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 ignificant 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-worldstructuredness.en_US
dc.subjectData Generation, Social Network Benchmark, Synthetic Data, Linked Data, Big Data, RDF, Benchmarksen_US
dc.titleAn RDF Dataset Generator for the Social Network Benchmark with Real-World Coherenceen_US
dc.typeProceeding articleen_US
dc.relation.conferenceWorkshop on Benchmarking Linked Data 2016en_US
item.grantfulltextopen-
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Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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