One reason is that the topic overlap of coordinated cross-lingual text streams is not so significant as the Wikipedia data used for their experiments, and the other reason is that their approaches focus on common fundamental words like "城市(city)" while our targets are OOVs like "东协(ASEAN)" which do not frequently appear in a corpus.
our approach is more practical: it not only works well in easily available and endless coordinated text streams without high content overlap requirement, but also can accurately mine translations of many OOVs which do not appear frequently and really need mining their translations.