The input of the model is a source text {x i } = x 1 , ..., x N , and the output is a sequence of summary words {y t } = y 1 , ..., y T , each of which is a symbol from the dictionary V. Online posts include lots of morphologically similar words, which should be closely embedded.
we use the fastText (Bojanowski et al., 2016) trained on the Common Crawl corpus, to initialize the word embedding matrix W emb .