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AAAI 2007

L2R: A Logical Method for Reference Reconciliation

Conference Paper Knowledge and Information Systems Artificial Intelligence

Abstract

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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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
1143903940200461098