A Multi-view Approach for Term Translation Spotting

  • Raphaël Rubino
  • Georges Linarès
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6609)


This paper presents a multi-view approach for term translation spotting, based on a bilingual lexicon and comparable corpora. We propose to study different levels of representation for a term: the context, the theme and the orthography. These three approaches are studied individually and combined in order to rank translation candidates. We focus our task on French-English medical terms. Experiments show a significant improvement of the classical context-based approach, with a F-score of 40.3% for the first ranked translation candidates.


Multilingualism Comparable Corpora Topic Model 


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  1. 1.
    Brown, P., Della Pietra, S., Della Pietra, V., Jelinek, F., Lafferty, J., Mercer, R., Roossin, P.: A Statistical Approach to Machine Translation. Computational Linguistics 16, 79–85 (1990)Google Scholar
  2. 2.
    Koehn, P.: Europarl: A Parallel Corpus for Statistical Machine Translation. In: MT Summit, vol. 5, Citeseer (2005)Google Scholar
  3. 3.
    Fung, P.: Compiling Bilingual Lexicon Entries from a Non-parallel English-Chinese Corpus. In: Proceedings of the 3rd Workshop on Very Large Corpora, pp. 173–183 (1995)Google Scholar
  4. 4.
    Rapp, R.: Identifying Word Translations in Non-parallel Texts. In: Proceedings of the 33rd ACL Conference, pp. 320–322. ACL (1995)Google Scholar
  5. 5.
    Chiao, Y., Zweigenbaum, P.: Looking for Candidate Translational Equivalents in Specialized, Comparable Corpora. In: Proceedings of the 19th Coling Conference, vol. 2, pp. 1–5. ACL (2002)Google Scholar
  6. 6.
    Rubino, R.: Exploring Context Variation and Lexicon Coverage in Projection-based Approach for Term Translation. In: Proceedings of the RANLP Student Research Workshop, Borovets, Bulgaria, pp. 66–70. ACL (2009)Google Scholar
  7. 7.
    Laroche, A., Langlais, P.: Revisiting Context-based Projection Methods for Term-translation Spotting in Comparable Corpora. In: Proceedings of the 23rd Coling Conference, Beijing, China, pp. 617–625 (2010)Google Scholar
  8. 8.
    Shao, L., Ng, H.: Mining New Word Translations from Comparable Corpora. In: Proceedings of the 20th ACL Conference, p. 618. ACL (2004)Google Scholar
  9. 9.
    Gaussier, E., Renders, J., Matveeva, I., Goutte, C., Dejean, H.: A Geometric View on Bilingual Lexicon Extraction from Comparable Corpora. In: Proceedings of the 42nd ACL Conference, p. 526. ACL (2004)Google Scholar
  10. 10.
    Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet Allocation. The Journal of Machine Learning Research 3, 993–1022 (2003)zbMATHGoogle Scholar
  11. 11.
    Levenshtein, V.: Binary Codes Capable of Correcting Deletions, Insertions, and Reversals. Soviet Physics Doklady 10, 707–710 (1966)zbMATHGoogle Scholar
  12. 12.
    Rapp, R.: Automatic Identification of Word Translations from Unrelated English and German Corpora. In: Proceedings of the 37th ACL Conference, pp. 519–526. ACL (1999)Google Scholar
  13. 13.
    Déjean, H., Gaussier, E., Renders, J., Sadat, F.: Automatic Processing of Multilingual Medical Terminology: Applications to Thesaurus Enrichment and Cross-language Information Retrieval. Artificial Intelligence in Medicine 33, 111–124 (2005)CrossRefGoogle Scholar
  14. 14.
    Koehn, P., Knight, K.: Learning a Translation Lexicon from Monolingual Corpora. In: Proceedings of the ACL Workshop on Unsupervised Lexical Acquisition, vol. 9, pp. 9–16. ACL (2002)Google Scholar
  15. 15.
    Church, K.W., Hanks, P.: Word Association Norms, Mutual Information, and Lexicography. Computational Linguistics 16(1), 22–29 (1990)Google Scholar
  16. 16.
    Dunning, T.: Accurate Methods for the Statistics of Surprise and Coincidence. Computational Linguistics 19, 61–74 (1993)Google Scholar
  17. 17.
    Evert, S.: The Statistics of Word Cooccurrences: Word Pairs and Collocations. Ph.D. Thesis, Institut für maschinelle Sprachverarbeitung, Universität Stuttgart (2004)Google Scholar
  18. 18.
    Fung, P., McKeown, K.: Finding Terminology Translations from Non-parallel Corpora. In: Proceedings of the 5th Workshop on Very Large Corpora, pp. 192–202 (1997)Google Scholar
  19. 19.
    Deerwester, S., Dumais, S., Furnas, G., Landauer, T., Harshman, R.: Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science 41, 391–407 (1990)CrossRefGoogle Scholar
  20. 20.
    Hofmann, T.: Probabilistic Latent Semantic Indexing. In: Proceedings of the 22nd ACM SIGIR Conference, pp. 50–57. ACM, New York (1999)Google Scholar
  21. 21.
    Ni, X., Sun, J., Hu, J., Chen, Z.: Mining Multilingual Topics from Wikipedia. In: Proceedings of the 18th International Conference on WWW, pp. 1155–1156. ACM, New York (2009)Google Scholar
  22. 22.
    Boyd-Graber, J., Blei, D.M.: Multilingual topic models for unaligned text. In: Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, pp. 75–82 (2009)Google Scholar
  23. 23.
    Langlais, P., Yvon, F., Zweigenbaum, P.: Translating medical words by analogy. In: Intelligent Data Analysis in Biomedicine and Pharmacology, Washington, DC, USA, pp. 51–56 (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Raphaël Rubino
    • 1
  • Georges Linarès
    • 1
  1. 1.Laboratoire Informatique d’AvignonAvignonFrance

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