About https://w3id.org/scholarlydata/inproceedings/iswc-2019-journal-429

Subject: https://w3id.org/scholarlydata/inproceedings/iswc-2019-journal-429Property: http://www.w3.org/1999/02/22-rdf-syntax-ns#typehttp://www.ontologydesignpatterns.org/ont/dul/DUL.owl#SocialObjecthttps://w3id.org/scholarlydata/ontology/conference-ontology.owl#InProceedingshttp://www.w3.org/2000/01/rdf-schema#Resourcehttp://www.ontologydesignpatterns.org/ont/dul/DUL.owl#InformationObjecthttp://www.ontologydesignpatterns.org/ont/dul/DUL.owl#Objecthttp://purl.org/spar/fabio/ProceedingsPaperhttp://www.w3.org/2002/07/owl#ThingProperty: http://www.w3.org/2000/01/rdf-schema#labelKnowMore - Knowledge Base Augmentation with Structured Web MarkupProperty: http://swrc.ontoware.org/ontology#abstractKnowledge bases are in widespread use for aiding tasks such as information extraction and information retrieval. However, knowledge bases are known to be inherently incomplete. As a complimentary data source, embedded entity markup based on Microdata, RDFa, and Microformats have become prevalent on the Web. RDF statements extracted from markup are fundamentally different from traditional knowledge graphs: entity descriptions are flat, facts are highly redundant and of varied quality, and, explicit links are missing despite a vast amount of coreferences. Therefore, data fusion is required in order to facilitate the use of markup data for KBA. We present a novel data fusion approach which addresses these issues. We perform a thorough evaluation on a subset of the Web Data Commons dataset and show significant potential for augmenting existing knowledge bases. A comparison with existing data fusion baselines demonstrates superior performance of our approach when applied to Web markup data. Property: http://purl.org/dc/elements/1.1/creatorhttps://w3id.org/scholarlydata/person/besnik-fetahuhttps://w3id.org/scholarlydata/person/ujwal-gadirajuhttps://w3id.org/scholarlydata/person/stefan-dietzehttps://w3id.org/scholarlydata/person/oliver-lehmberghttps://w3id.org/scholarlydata/person/ran-yuhttps://w3id.org/scholarlydata/person/dominique-ritzeProperty: http://purl.org/dc/elements/1.1/subjectKnowledge base augmentation Web markup data fusion entity resolutionProperty: http://purl.org/dc/elements/1.1/titleKnowMore - Knowledge Base Augmentation with Structured Web MarkupProperty: http://purl.org/ontology/bibo/authorListhttps://w3id.org/scholarlydata/authorlist/iswc-2019-journal-429Property: http://xmlns.com/foaf/0.1/makerhttps://w3id.org/scholarlydata/person/stefan-dietzehttps://w3id.org/scholarlydata/person/ujwal-gadirajuhttps://w3id.org/scholarlydata/person/ran-yuhttps://w3id.org/scholarlydata/person/besnik-fetahuhttps://w3id.org/scholarlydata/person/dominique-ritzehttps://w3id.org/scholarlydata/person/oliver-lehmbergProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#abstractKnowledge bases are in widespread use for aiding tasks such as information extraction and information retrieval. However, knowledge bases are known to be inherently incomplete. As a complimentary data source, embedded entity markup based on Microdata, RDFa, and Microformats have become prevalent on the Web. RDF statements extracted from markup are fundamentally different from traditional knowledge graphs: entity descriptions are flat, facts are highly redundant and of varied quality, and, explicit links are missing despite a vast amount of coreferences. Therefore, data fusion is required in order to facilitate the use of markup data for KBA. We present a novel data fusion approach which addresses these issues. We perform a thorough evaluation on a subset of the Web Data Commons dataset and show significant potential for augmenting existing knowledge bases. A comparison with existing data fusion baselines demonstrates superior performance of our approach when applied to Web markup data. Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#hasAuthorListhttps://w3id.org/scholarlydata/authorlist/iswc-2019-journal-429Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#isPartOfhttps://w3id.org/scholarlydata/conference/iswc/2019/proceedingsProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#keywordKnowledge base augmentation Web markup data fusion entity resolutionProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#titleKnowMore - Knowledge Base Augmentation with Structured Web MarkupProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#relatesToEventhttps://w3id.org/scholarlydata/talk/iswc-2019-journal-429
Subject: https://w3id.org/scholarlydata/conference/iswc/2019/proceedingsProperty: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#hasParthttps://w3id.org/scholarlydata/inproceedings/iswc-2019-journal-429
Subject: https://w3id.org/scholarlydata/role-during-event/iswc2019-author-besnik-fetahu-iswc-2019-journal-429Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#withDocumenthttps://w3id.org/scholarlydata/inproceedings/iswc-2019-journal-429
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Subject: https://w3id.org/scholarlydata/role-during-event/iswc2019-author-stefan-dietze-iswc-2019-journal-429Property: https://w3id.org/scholarlydata/ontology/conference-ontology.owl#withDocumenthttps://w3id.org/scholarlydata/inproceedings/iswc-2019-journal-429
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Subject: https://w3id.org/scholarlydata/person/stefan-dietzeProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/iswc-2019-journal-429
Subject: https://w3id.org/scholarlydata/person/dominique-ritzeProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/iswc-2019-journal-429
Subject: https://w3id.org/scholarlydata/person/besnik-fetahuProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/iswc-2019-journal-429
Subject: https://w3id.org/scholarlydata/person/ujwal-gadirajuProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/iswc-2019-journal-429
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Subject: https://w3id.org/scholarlydata/person/oliver-lehmbergProperty: http://xmlns.com/foaf/0.1/madehttps://w3id.org/scholarlydata/inproceedings/iswc-2019-journal-429