2013
DOI: 10.1007/978-3-642-41242-4_2
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ParlBench: A SPARQL Benchmark for Electronic Publishing Applications

Abstract: Abstract. ParlBench is a scalable RDF benchmark modelling a large scale electronic publishing scenario. The benchmark offers large collections of the Dutch parliamentary proceedings together with information about members of the parliament and political parties. The data is real, but free of intellectual property rights issues. On top of the benchmark data sets, several realistic application benchmarks as well as targeted micro benchmarks can be developed. This paper describes the benchmark data sets and 28 an… Show more

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Cited by 4 publications
(4 citation statements)
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“…RDFs unambiguously identify objects, such as people, locations, or abstract concepts, and describe the nature of their relation in the form of subject-predicate-object triples. Besides modelling the parliamentary debates as RDF triples, we will integrate it into other relevant vocabularies (FOAF,19 DBpedia Ontology, 20 BIO 21 ) (Tarasova and Marx, 2013).…”
Section: Irrigation South Saskatchewan River Motion For Adjournmentmentioning
confidence: 99%
“…RDFs unambiguously identify objects, such as people, locations, or abstract concepts, and describe the nature of their relation in the form of subject-predicate-object triples. Besides modelling the parliamentary debates as RDF triples, we will integrate it into other relevant vocabularies (FOAF,19 DBpedia Ontology, 20 BIO 21 ) (Tarasova and Marx, 2013).…”
Section: Irrigation South Saskatchewan River Motion For Adjournmentmentioning
confidence: 99%
“…The documents vary a lot in their internal structure and size: from 3 Kbytes to 160 Kbytes, with an average size of about 60 Kbytes. We compared the outcomes of the algorithm with a hand-crafted gold standard created by studying the XML vocabulary originally used to mark up the documents, and by associating each of its elements with one or more DoCO structures 39 . The overall results of this test were encouraging, since the 37 The algorithm (fully introduced in [15]) is neither an intelligent nor an adaptive algorithm, but rather a prescriptive one that uses the logical characterisations of DoCO components as a basis to identify them in documents through an iterative process.…”
Section: Retrieving Structures From Xml Sourcesmentioning
confidence: 99%
“…it/2013/doco/test. 39 We acknowledge that this analysis was subjective and solely based on our understanding of the semantics of the element, its definition schema and its documentation.…”
Section: Retrieving Structures From Xml Sourcesmentioning
confidence: 99%
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