Learning Co-reference Relations for FOAF Instances

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dc.contributor.authorSleeman, Jennifer
dc.contributor.authorFinin, Tim
dc.date.accessioned2018-11-20T17:32:57Z
dc.date.available2018-11-20T17:32:57Z
dc.date.issued2010-11-09
dc.descriptionProceedings of the Poster and Demonstration Session at the 9th International Semantic Web Conferenceen_US
dc.description.abstractFOAF is widely used on the Web to describe people, groups and organizations and their properties. Since FOAF does not require unique IDs, it is often unclear when two FOAF instances are co-referent, i.e., denote the same entity in the world. We describe a prototype system that identifies sets of co-referent FOAF instances using logical constraints (e.g., IFPs), strong heuristics (e.g., FOAF agents described in the same file are not co-referent), and a Support Vector Machine (SVM) generated classifier.en_US
dc.description.sponsorshipPartial support for this research was provided by NSF award 0910838 and the Johns Hopkins University Human Language Technology Center of Excellence.en_US
dc.description.urihttps://ebiquity.umbc.edu/paper/html/id/503/Learning-Co-reference-Relations-for-FOAF-Instancesen_US
dc.format.extent4 pagesen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/M2SF2MG4P
dc.identifier.urihttp://hdl.handle.net/11603/12069
dc.language.isoen_USen_US
dc.publisherCEURen_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.subjectThe friend of a friend (FOAF)en_US
dc.subjectmachine learningen_US
dc.subjectlinked dataen_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleLearning Co-reference Relations for FOAF Instancesen_US
dc.typeTexten_US

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