That is, where • indicates inner product operation and We use term-frequency-based encoding to obtain the sparse embedding s k i:j for each phrase.
we largely follow DrQA  to construct 2-gram-based tf-idf, resulting in a highly sparse representation (d d ≈16M) for each document.