Learning linear ordering problems for better translation
Roy W. Tromble, Jason M. Eisner · 2009
We apply machine learning to the Linear Ordering Problem in order to learn sentence-specific reordering models for machine translation. We demonstrate that even when these models are used as a mere preprocessing step for German-English translation, they significantly outperform Moses' integrated lexicalized reordering model.