Cluster-based Instance Consolidation For Subsequent Matching

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dc.contributor.authorSleeman, Jennifer
dc.contributor.authorFinin, Tim
dc.date.accessioned2018-11-05T15:23:32Z
dc.date.available2018-11-05T15:23:32Z
dc.date.issued2012-11-11
dc.descriptionFirst International Workshop on Knowledge Extraction and Consolidation from Social Mediaen_US
dc.description.abstractInstance consolidation is a way to merge instances that are thought to be the same or closely related that can be used to support coreference resolution and entity linking. For Semantic Web data, consolidating instances can be as simple as relating instances using owl:sameAs, as is the case in linked data, or merging instances that could then be used to populate or enrich a knowledge model. In many applications, systems process data incrementally over time and as new data is processed, the state of the knowledge model changes. Previous consolidations could prove to be incorrect. Consequently, a more abstract representation is needed to support instance consolidation. We describe our current research to perform consolidation that includes temporal support, support to resolve conflicts and an abstract representation of an instance that is the aggregate of a cluster of matched instances. We believe that this model will prove flexible enough to handle sparse instance data and can improve the accuracy of the knowledge model over time.en_US
dc.description.urihttps://ebiquity.umbc.edu/paper/html/id/603/Cluster-based-Instance-Consolidation-For-Subsequent-Matchingen_US
dc.format.extent6 pagesen_US
dc.genreconference papers and proceedings pre-printen_US
dc.identifierdoi:10.13016/M2HD7NX02
dc.identifier.citationJennifer Sleeman and Tim Finin, Cluster-based Instance Consolidation For Subsequent Matching, First International Workshop on Knowledge Extraction and Consolidation from Social Media, November 2012, Boston.en_US
dc.identifier.urihttp://hdl.handle.net/11603/11858
dc.language.isoen_USen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectInstance consolidationen_US
dc.subjectentityen_US
dc.subjectSemantic Weben_US
dc.subjectClusteren_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleCluster-based Instance Consolidation For Subsequent Matchingen_US
dc.typeTexten_US

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