Given a query token t q and the j-th position in post p, we compute the interaction scores by taking the cosine similarity between the word embeddings of token t q and post tokens t p j:j+k−1 from position j to j + k − 1: where S j ∈ R k×1 and k is the width of the convolutional kernel we are learning.
for each token in the post within the window, we compute its cosine similarity with query token t q .