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dc.contributor.authorPareti, Paolo
dc.contributor.authorKlein, Ewan
dc.contributor.authorBarker, Adam David
dc.date.accessioned2015-10-01T23:13:13Z
dc.date.available2015-10-01T23:13:13Z
dc.date.issued2015-06-28
dc.identifier220438078
dc.identifier4e3d4a65-ccb2-4d1b-8d44-9bbc4b1320c1
dc.identifier84978161958
dc.identifier.citationPareti , P , Klein , E & Barker , A D 2015 , A Linked Data scalability challenge : concept reuse leads to semantic decay . in Proceedings of the ACM Web Science Conference . , 7 , ACM , New York , WebSci'15 ACM Web Science Conference , Oxford , United Kingdom , 28/06/15 . https://doi.org/10.1145/2786451.2786485en
dc.identifier.citationconferenceen
dc.identifier.isbn9781450336727
dc.identifier.urihttps://hdl.handle.net/10023/7586
dc.description.abstractThe increasing amount of available Linked Data resources is laying the foundations for more advanced Semantic Web applications. One of their main limitations, however, remains the general low level of data quality. In this paper we focus on a measure of quality which is negatively affected by the increase of the available resources. We propose a measure of semantic richness of Linked Data concepts and we demonstrate our hypothesis that the more a concept is reused, the less semantically rich it becomes. This is a significant scalability issue, as one of the core aspects of Linked Data is the propagation of semantic information on the Web by reusing common terms. We prove our hypothesis with respect to our measure of semantic richness and we validate our model empirically. Finally, we suggest possible future directions to address this scalability problem.
dc.format.extent5
dc.format.extent765044
dc.language.isoeng
dc.publisherACM
dc.relation.ispartofProceedings of the ACM Web Science Conferenceen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subject3rd-DASen
dc.subject.lccQA75en
dc.titleA Linked Data scalability challenge : concept reuse leads to semantic decayen
dc.typeConference itemen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.identifier.doi10.1145/2786451.2786485


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