This potentially alleviates the data sparseness problem since there are usually a large number of reordering training examples available (Xiong et al., 2006).
the MaxEnt ITG model and its extensions (Xiong et al., 2008;Xiong et al., 2010) have achieved competing performance as compared with state-of-the-art phrase-based systems.