To learn the word embedding, we use the following objective function, which requires that for each context word w j there is a sequence of parallel hyperplanes that separate the representations of the words in W j i−1 from the representations of the words in j for each j.
we make the assumption that the higher PPMI(w, w j ) the stronger w is related to w j , but we do not otherwise assume that the numerical value of PPMI(w, w j ) is relevant.