In order to dynamically point to more related messages in the thread history, we use an one-way attention, which has been successfully adopted in many NLP tasks (Tan et al., 2016;Hermann et al., 2015).
given the sequence outputs of each thread's LSTM, {h l (l,k) } K k=1 , we perform a weighted mean pooling to get a context embedding e l cxt , attended by the one-step LSTMencoded m i , denoted asĥ i .