Spectral Clustering for Example Based Machine Translation

  title={Spectral Clustering for Example Based Machine Translation},
  author={Rashmi Gangadharaiah and Ralf D. Brown and Jaime G. Carbonell},
Prior work has shown that generalization of data in an Example Based Machine Translation (EBMT) system, reduces the amount of pre-translated text required to achieve a certain level of accuracy (Brown, 2000). Several word clustering algorithms have been suggested to perform these generalizations, such as kMeans clustering or Group Average Clustering. The hypothesis is that better contextual clustering can lead to better translation accuracy with limited training data. In this paper, we use a… CONTINUE READING
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