The reference reconciliation problem consists in deciding
whether different identifiers refer to the same data,
i.e., correspond to the same world entity. The L2R system
exploits the semantics of a rich data model, which
extends RDFS by a fragment of OWL-DL and SWRL
rules. In L2R, the semantics of the schema is translated
into a set of logical rules of reconciliation, which are
then used to infer correct decisions both of reconciliation
and no reconciliation. In contrast with other approaches,
the L2R method has a precision of 100% by
construction. First experiments show promising results
for recall, and most importantly significant increases
when rules are added.



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  ° Intégration d'informations

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  ° Intelligence Artificielle et Systèmes d'Inférence

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  ° SAÏS Fatiha