For the auxiliary opinion detection task, we feed r L o,i into a softmax layer for predicting the probability scores z O i ∈ R |Y O | over the opinion labels 2 Y O , i.e., a word is an opinion word or not, as: To adapt the captured relations to be domaininvariant, we propose a Selective Adversarial Learning (SAL) method to dynamically align the words with high probability to fall into the aspect boundaries, i.e., being an aspect word.
we introduce a domain discriminator for each word, which aims to identify the domain label y D i ∈ R |Y D | of the input word, i.e., the word in the sentence is from the source or the target domain.