L2R: A Logical Method for Reference Reconciliation

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.

• Type: Conference
• Year: 2007
• Where: AAAI
• Authors: Fatiha Saïs, Nathalie Pernelle, Marie-Christine Rousset
• Keywords: AAAI 2007, Intelligent Agents, L2R Method, Reference Reconciliation Problem, Rich Data Model