Automatic term pair extraction from bilingual patent corpus

Yuen Hsien Tseng, Chao Lin Liu, Ze Jing Chuang

Research output: Contribution to conferencePaperpeer-review


This paper proposes two approaches to extract translation term pairs from Chinese-English bilingual corpus with more than 500,000 patents. One approach is precision-oriented, in which we compare six term alignment methods. Based on our experiments, we find that the EM (Expectation Maximization) method is the best. However, it is time-consuming and hard to extract many-to-many translations for the same concept. While the MI (mutual information) method performs worst, the term pairs extracted may be totally different from those by EM. This may inspire subsequent researches to study the possibility of hybrid term alignment methods. The other approach is recall-oriented, in which a simple idea was proposed. With an efficient implementation, 20% more term pairs were extracted based on an existing lingual lexicon which already has more than one million term pairs merged from several sources.

Original languageEnglish
Number of pages14
Publication statusPublished - 2009
Event21st Conference on Computational Linguistics and Speech Processing, ROCLING 2009 - Taichung, Taiwan
Duration: 2009 Sept 12009 Sept 2


Other21st Conference on Computational Linguistics and Speech Processing, ROCLING 2009


  • Cross-lingual patent analysis
  • Machine translation
  • Patent corpus
  • Term alignment
  • Term extraction

ASJC Scopus subject areas

  • Language and Linguistics
  • Speech and Hearing


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