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dc.contributor.authorDing, Li
dc.contributor.authorFinin, Timothy
dc.contributor.authorPeng, Yun
dc.contributor.authorPinheiro, Paulo
dc.contributor.authorMcGuinness, Deborah
dc.date.accessioned2022-02-18T02:40:38Z
dc.date.available2022-02-18T02:40:38Z
dc.date.issued2005-11-06
dc.identifier.other358
dc.identifier.urihttp://archive.tw.rpi.edu/media/latest/ding2005Tracking_RDF_Graph_Provenance_using_RDF_Molecule.pdf
dc.identifier.urihttps://hdl.handle.net/20.500.13015/4760
dc.description.abstractThe Semantic Web facilitates integrating partial knowledge and finding evidence for hypothesis from web knowledge sources. However, the appropriate level of granularity for tracking provenance of RDF graph remains in debate. RDF document is too coarse since it could contain irrelevant information. RDF triple will fail when two triples share the same blank node. Therefore, this paper investigates lossless decomposition of RDF graph and tracking the provenance of RDF graph using RDF molecule, which is the finest and lossless component of an RDF graph. A sub-graph is lossless if it can be used to restore the original graph without introducing new triples. A sub-graph is finest if it cannot be further decomposed into lossless sub-graphs. The lossless decomposition algorithms and RDF molecule have been formalized and implemented by a prototype RDF graph provenance service in Swoogle project.
dc.relation.urihttps://tw.rpi.edu/project/InferenceWeb
dc.subjectInference Web
dc.titleTracking RDF Graph Provenance using RDF Molecules


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