We use TF•IDF to define the weighting function, where we regard each context window of the word as a short document to calculate the document frequency.
for a word w 0 , each of its context window can be de- Then we represent the window by calculating the weighted average of the pre-learned embedding vectors of the context words as the TF•IDF score of w i , and v w i is the pre-learned embedding vector of w i .