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Matching Multi-lingual Subject Vocabularies

  • Shenghui Wang
  • Antoine Isaac
  • Balthasar Schopman
  • Stefan Schlobach
  • Lourens van der Meij
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5714)

Abstract

Most libraries and other cultural heritage institutions use controlled knowledge organisation systems, such as thesauri, to describe their collections. Unfortunately, as most of these institutions use different such systems, unified access to heterogeneous collections is difficult. Things are even worse in an international context when concepts have labels in different languages. In order to overcome the multilingual interoperability problem between European Libraries, extensive work has been done to manually map concepts from different knowledge organisation systems, which is a tedious and expensive process.

Within the TELplus project, we developed and evaluated methods to automatically discover these mappings, using different ontology matching techniques. In experiments on major French, English and German subject heading lists Rameau, LCSH and SWD, we show that we can automatically produce mappings of surprisingly good quality, even when using relatively naive translation and matching methods.

Keywords

Ontology Match Concept Label Common Extension Instance Match Concept Coverage 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Shenghui Wang
    • 1
    • 2
  • Antoine Isaac
    • 1
    • 2
  • Balthasar Schopman
    • 1
  • Stefan Schlobach
    • 1
  • Lourens van der Meij
    • 1
    • 2
  1. 1.Vrije Universiteit AmsterdamNetherlands
  2. 2.Koninklijke Bibliotheek, den HaagNetherlands

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