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dc.contributor.authorOren, Eyalen
dc.contributor.authorGerke, Sebastianen
dc.contributor.authorDecker, Stefanen
dc.identifier.citationEyal Oren, Sebastian Gerke, Stefan Decker "Simple algorithms for predicate suggestions using similarity and co-occurrence", Proceedings of the European Semantic Web Conference, 2007.en
dc.description.abstractWhen creating Semantic Web data, users have to make a critical choice for a vocabulary: only through shared vocabularies can meaning be established. A centralised policy prevents terminology divergence but would restrict users needlessly. As seen in collaborative tagging environments, suggestion mechanisms help terminology convergence without forcing users. We introduce two domain-independent algorithms for recommending predicates (RDF statements) about resources, based on statistical dataset analysis. The first algorithm is based on similarity between resources, the second one is based on co-occurrence of predicates. Experimental evaluation shows very promising results: a high precision with relatively high recall in linear runtime performance.en
dc.publisherAssociation for Computing Machineryen
dc.subject.lcshSemantic weben
dc.titleSimple algorithms for predicate suggestions using similarity and co-occurrenceen
dc.typeConference Paperen
dc.local.publisherstatementauthor's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 4th European conference on The Semantic Web: Research and Applications
dc.contributor.funderScience Foundation Irelanden

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