These features are carefully designed to reduce the data sparseness problem and some of them are inspired by previous work ( He et al. , 2008 ; Gimpel and Smith , 2008 ; Marton and Resnik , 2008 ; Chiang et al. , 2009 ; Setiawan et al. , 2009 ; Shen et al. , 2009 ; Xiong et al. , 2009 ) : 1 .
rich sourceside context for statistical machine translation
Kevin Gimpel Noah A Smith
We incorporate into the ME based model the following informative context-based features to train CBSM and CBTM . These features are carefully designed to reduce the data sparseness problem and some of them are inspired by previous work ( He et al. , 2008 ; Gimpel and Smith , 2008 ; Marton and Resnik , 2008 ; Chiang et al. , 2009 ; Setiawan et al. , 2009 ; Shen et al. , 2009 ; Xiong et al. , 2009 ) : 1 . Function word features , which indicate whether the hierarchical source-side/targetside rule strings and sub-phrases covered by non-terminals contain function words that are often important clues of predicting syntactic structures .
These features are carefully designed to reduce the data sparseness problem and some of them are inspired by previous work ( He et al. , 2008 ; @@CITATION ; Marton and Resnik , 2008 ; Chiang et al. , 2009 ; Setiawan et al. , 2009 ; Shen et al. , 2009 ; Xiong et al. , 2009 ) : 1 .