Reflections on: Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization

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dc.contributor.authorPadia, Ankur
dc.contributor.authorKalpakis, Konstantinos
dc.contributor.authorFerraro, Francis
dc.contributor.authorFinin, Tim
dc.date.accessioned2020-07-22T17:19:47Z
dc.date.available2020-07-22T17:19:47Z
dc.descriptionInternational Semantic Web Conference 2019
dc.description.abstractWe present a family of four novel methods for embedding knowledge graphs into real-valued tensors that capture the ordered relations found in RDF. Unlike many previous models, these can easily use prior background knowledge from users or existing knowledge graphs. We demonstrate our models on the task of predicting new facts on eight different knowledge graphs, achieving a 5% to 50% improvement over existing systems. Through experiments, we derived recommendations for selecting the best model based on knowledge graph characteristics. We also give a provably-convergent, linear tensor factorization algorithm.en_US
dc.description.urihttp://ceur-ws.org/Vol-2576/paper09.pdfen_US
dc.format.extent9 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.identifierdoi:10.13016/m2icwr-r8p8
dc.identifier.citationAnkur Padia, Konstantinos Kalpakis, Francis Ferraro and Tim Finin, Reflections on: Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization, http://ceur-ws.org/Vol-2576/paper09.pdfen_US
dc.identifier.urihttp://hdl.handle.net/11603/19220
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.rightsAttribution 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectUMBC Ebiquity Research Group
dc.titleReflections on: Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorizationen_US
dc.typeTexten_US

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