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1 SHAMAN - Symbolic and Human-centric view of dAta MANagement IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE

Abstract : Finding the commonalities between descriptions of data or knowledge is a foundational reasoning problem of Machine Learning introduced in the 70-s, which amounts to computing a least general generalization lgg of such descriptions. It has also started receiving consideration in Knowlegge Representation from the 90-s, and recently in the Semantic Web field. We revisit this problem in the popular Resource Description Framework RDF of W3C, where descriptions are RDF graphs, i.e., a mix of data and knowledge. Notably, and in contrast to the literature, our solution to this problem holds for the entire RDF standard, i.e., we do not restrict RDF graphs in any way neither their structure nor their semantics based on RDF entailment, i.e., inference and, further, our algorithms can compute lggs of small-to-huge RDF graphs.

Keywords : RDF RDFS RDF entailment Least general generalization

Autor: Sara El Hassad - François Goasdoué - Hélène Jaudoin -

Fuente: https://hal.archives-ouvertes.fr/


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