We use four context encoders in our model, namely, averaged embedding, RNN (Pearlmutter, 1989), attention (Bahdanau et al., 2014), and memory networks (Weston et al., 2015), which are proven useful in text representation Weston et al., 2015;Nie et al., 2017).
in this task, to the best of our knowledge, we are the first to encode conversations for detecting keyphrases in microblog posts.