In this paper, we propose a reinforced bidirectional attention network approach to tackle the above two challenges.
we first propose a word selection model, namely Reinforced Aspect-relevant Word Selector (RAWS), to alleviate the effects of noisy words for a specific aspect through discarding noisy words and only select aspect-relevant words in a word sequence.