Each word will be represented by a comparatively low-dimentional real-valued vector and the lexical similarity between words can be evaluated by the Euclidean distance between their correspondent vectors (Mikolov et al., 2013;Pennington et al., 2014).
word vectors can be used as lexical features in various NLP applications and have achieved many positive results (Collobert et al., 2011;Maas et al., 2011).