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Journal Articles The VLDB Journal Year : 2020

RDF graph summarization for first-sight structure discovery

Abstract

To help users get familiar with large RDF graphs, RDF summarization techniques can be used. In this work, we study quotient summaries of RDF graphs, that is: graph summaries derived from a notion of equivalence among RDF graph nodes. We make the following contributions: (i) four novel summaries which are often small and easy-to-comprehend, in the style of E--R diagrams; (ii) efficient (amortized linear-time) algorithms for computing these summaries either from scratch, or incrementally, reflecting additions to the graph; (iii) the first formal study of the interplay between RDF graph saturation in the presence of an RDFS ontology, and summarization; we provide a sufficient condition for a highly efficient shortcut method to build the quotient summary of a graph without saturating it; (iv) formal results establishing the shortcut conditions for some of our summaries and others from the literature; (v) experimental validations of our claim within a tool available online.
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Dates and versions

hal-02530206 , version 1 (02-04-2020)
hal-02530206 , version 2 (24-08-2020)

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François Goasdoué, Pawel Guzewicz, Ioana Manolescu. RDF graph summarization for first-sight structure discovery. The VLDB Journal, 2020, 29 (5), pp.1191-1218. ⟨10.1007/s00778-020-00611-y⟩. ⟨hal-02530206v2⟩
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