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Conference Papers Year : 2020

Dissimilarity-based approach for Identity Link Invalidation


More and more datasets are currently connected by identity links using properties such as owl:sameAs expressed in OWL. Identity links are statements that declare that two resources refer to the same real-world entity. However, we cannot attest the correctness of all identity links. Without a central name authority, most of identity links are generated by heuristics and they are not reviewed by experts. The main issue in invalidating identity links is the heterogeneity of datasets, they commonly do not share the same predicates and the description of resources can be incomplete. Despite how the resources are described, identity links are necessary to link data and posterior reuse. In this paper, we present here a framework to invalidate identity links by dissimilarity and outlier detection in equivalence classes of identity links.
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Dates and versions

hal-04420906 , version 1 (27-01-2024)



  • HAL Id : hal-04420906 , version 1


Anderson Carlos Ferreira da Silva, Fatiha Saïs, Emmanuel Waller, Frédéric Andrès. Dissimilarity-based approach for Identity Link Invalidation. IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), Sep 2020, Bayonne, France. ⟨hal-04420906⟩
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