oMAP: Combining Classifiers for Aligning Automatically OWL Ontologies

  • Umberto Straccia
  • Raphaël Troncy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3806)

Abstract

This paper introduces a method and a tool for automatically aligning OWL ontologies, a crucial step for achieving the interoperability of heterogeneous systems in the Semantic Web. Different components are combined for finding suitable mapping candidates (together with their weights), and the set of rules with maximum matching probability is selected. Machine learning-based classifiers and a new classifier using the structure and the semantics of the OWL ontologies are proposed. Our method has been implemented and evaluated on an independent test set provided by an international ontology alignment contest. We provide the results of this evaluation with respect to the other competitors.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Umberto Straccia
    • 1
  • Raphaël Troncy
    • 1
    • 2
  1. 1.ISTI-CNRPisaItaly
  2. 2.CWI AmsterdamAmsterdamThe Netherlands

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