For a specific aspect term, the domain-invariant feature based on the aspect-opinion attention contains more information of its corresponding opinion words, which is beneficial to the final aspectlevel sentiment classification.
we first calculate the position representation of a specific aspect term with its position x a and the sentimentdominant context H c : where x a = {0 1 , ..., 1 i+1 , ..., 1 i+m , ...0 n } represents the word positions of an aspect subsequence in the input sentence x with non-zero values and m is the length of the aspect.