<cite>Duong et al. (2016)</cite> constructed bilingual word embeddings based on monolingual data and PanLex. In this way, <cite>their</cite> approach can be applied to more languages as PanLex covers more than a thousand languages. <cite>They</cite> solve the polysemy problem by integrating an EM algorithm for selecting a lexicon. Relative to many previous crosslingual word embeddings, <cite>their</cite> joint training algorithm achieved state-of-the-art performance for the bilingual lexicon induction task, performing significantly better on monolingual similarity and achieving a competitive result on cross lingual document classification.