A Method to Combine Linguistic Ontology-Mapping Techniques

  • Willem Robert van Hage
  • Sophia Katrenko
  • Guus Schreiber
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3729)


We discuss four linguistic ontology-mapping techniques and evaluate them on real-life ontologies in the domain of food. Furthermore we propose a method to combine ontology-mapping techniques with high Precision and Recall to reduce the necessary amount of manual labor and computation.


Animal Product Resource Description Framework Food Category Ontology Mapping Geographical Domain 
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.


  1. 1.
    Brickley, D., Guha, R.: Resource description framework (RDF) schema specification 1.0. W3C (March 2000)Google Scholar
  2. 2.
    Brin, S.: Extracting patterns and relations from the world wide web. In: Schek, H.-J., Saltor, F., Ramos, I., Alonso, G. (eds.) EDBT 1998. LNCS, vol. 1377. Springer, Heidelberg (1998)Google Scholar
  3. 3.
    Cimiano, P., Staab, S.: Learning by googling. SIGKDD Explor. Newsl. 6(2), 24–33 (2004)CrossRefGoogle Scholar
  4. 4.
    Hearst, M.: Automatic acquisition of hyponyms from large text corpora. In: Proceedings of the 14th International Conference on Computational Linguistics (1992)Google Scholar
  5. 5.
    Kalfoglou, Y., Schorlemmer, M.: Ontology mapping: the state of the art. The knowledge engineering review 18(1), 1–31 (2003)CrossRefGoogle Scholar
  6. 6.
    Kamps, J.: Improving retrieval effectiveness by reranking documents based on controlled vocabulary. In: McDonald, S., Tait, J.I. (eds.) ECIR 2004. LNCS, vol. 2997, pp. 283–295. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Lin, D.: Dependency-based evaluation of minipar. In: Proceedings of the Workshop on the Evaluation of Parsing Systems, First International Conference on Language Resources and Evaluation, Granada, Spain (May 1998)Google Scholar
  8. 8.
    Rahm, E., Bernstein, P.A.: A survey of approaches to automatic schema matching. VLDB Journal 10(4) (2001)Google Scholar
  9. 9.
    Schmid, H.: Probabilistic part-of-speech tagging using decision trees. In: Proc. of International Conference on New Methods in Language Processing (1994)Google Scholar
  10. 10.
    Stuckenschmidt, H., van Harmelen, F., de Waard, A., Scerri, T., Bhogal, R., van Buel, J., Crowlesmith, I., Fluit, C., Kampman, A., Broekstra, J., van Mulligen, E.: Exploring large document repositories with rdf technology: The dope project. IEEE Intelligent Systems 19(3), 34–40 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Willem Robert van Hage
    • 1
  • Sophia Katrenko
    • 2
  • Guus Schreiber
    • 3
  1. 1.TNO, Science and Industry 
  2. 2.Computer ScienceFree University Amsterdam 
  3. 3.Informatics InstituteUniversity of Amsterdam 

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