Our approach is based on the GloVe model for word embedding (Pennington et al., 2014).
we also associate two vectors with each word i: the vector w i , which intuitively represents the meaning of word i, and the vectorw j , which intuitively represents how the occurrence of i in the context of another word j affects the meaning of that word.