SCARLET: SemantiC RelAtion DiscoveRy by Harvesting OnLinE OnTologies

  • Marta Sabou
  • Mathieu d’Aquin
  • Enrico Motta
Conference paper

DOI: 10.1007/978-3-540-68234-9_72

Volume 5021 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Sabou M., d’Aquin M., Motta E. (2008) SCARLET: SemantiC RelAtion DiscoveRy by Harvesting OnLinE OnTologies. In: Bechhofer S., Hauswirth M., Hoffmann J., Koubarakis M. (eds) The Semantic Web: Research and Applications. ESWC 2008. Lecture Notes in Computer Science, vol 5021. Springer, Berlin, Heidelberg

Abstract

We present a demo of SCARLET, a technique for discovering relations between two concepts by harvesting the Semantic Web, i.e., automatically finding and exploring multiple and heterogeneous online ontologies. While we have primarily used SCARLET’s relation discovery functionality to support ontology matching and enrichment tasks, it is also available as a stand alone component that can potentially be integrated in a wide range of applications. This demo will focus on presenting SCARLET’s functionality and its different parametric settings that can influence the trade-off between its accuracy and time performance.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Marta Sabou
    • 1
  • Mathieu d’Aquin
    • 1
  • Enrico Motta
    • 1
  1. 1.Knowledge Media Institute (KMi)The Open UniversityMilton Keynes