Translation Selection Through Machine Learning with Language Resources

  • Hyun Ah Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4285)


Knowledge acquisition is a critical problem for machine translation and translation selection. In this paper, I propose a tranlsation selection method that combines variable features from multiple language resources using machine learning. I introduce multiple measures for sense disambiguation and word selection that are based on language resources, and apply machine learning to combine those measures for translation selection. In evaluation, precision of translation selection improves even though a small-sized bilingual corpus is used as training data.


Translation Selection Knowledge Acquisition Problem Machine Readable Dictionary Target Language Corpus Machine Learning 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hyun Ah Lee
    • 1
  1. 1.School of Computer and Software Engineering, Kumoh National Institute of TechnologyGyeongbukRepublic of Korea

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