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IJCNLP
2005
Springer

Improving Statistical Word Alignment with Ensemble Methods

8 years 11 months ago
Improving Statistical Word Alignment with Ensemble Methods
Abstract. This paper proposes an approach to improve statistical word alignment with ensemble methods. Two ensemble methods are investigated: bagging and cross-validation committees. On these two methods, both weighted voting and unweighted voting are compared under the word alignment task. In addition, we analyze the effect of different sizes of training sets on the bagging method. Experimental results indicate that both bagging and cross-validation committees improve the word alignment results regardless of weighted voting or unweighted voting. Weighted voting performs consistently better than unweighted voting on different sizes of training sets.
Hua Wu, Haifeng Wang
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where IJCNLP
Authors Hua Wu, Haifeng Wang
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