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Identity in RDF knowledge graphs : propagation of properties between contextually identical entities

Abstract : Due to a large number of knowledge graphs and, more importantly, their even more numerous interconnections using the owl:sameas property, it has become increasingly evident that this property is often misused. Indeed, the entities linked by the owl:sameas property must be identical in all possible and imaginable contexts. This is not always the case and leads to a deterioration of data quality. Identity must be considered as context-dependent. We have, therefore, proposed a large-scale study on the presence of semantics in knowledge graphs since specific semantic characteristics allow us to deduce identity links. This study naturally led us to build an ontology allowing us to describe the semantic content of a knowledge graph. We also proposed a interlinking approach based both on the logic allowed by semantic definitions, and on the predominance of certain properties to characterize the identity relationship between two entities. We looked at completeness and proposed an approach to generate a conceptual schema to measure the completeness of an entity. Finally, using our previous work, we proposed an approach based on sentence embedding to compute the properties that can be propagated in a specific context. Hence, the propagation framework allows the expansion of SPARQL queries and, ultimately, to increase the completeness of query results.
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https://tel.archives-ouvertes.fr/tel-03278909
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Submitted on : Tuesday, July 6, 2021 - 9:45:10 AM
Last modification on : Tuesday, July 13, 2021 - 3:28:21 AM

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PARIS_Pierre_Henri_2020.pdf
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  • HAL Id : tel-03278909, version 1

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Pierre-Henri Paris. Identity in RDF knowledge graphs : propagation of properties between contextually identical entities. Programming Languages [cs.PL]. Sorbonne Université; Cnam, 2020. English. ⟨NNT : 2020SORUS132⟩. ⟨tel-03278909⟩

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