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Aspect-level sentiment classification aims to identify the sentimentexpressed towards some aspects given context sentences. In this paper, weintroduce an attention-over-attention (AOA) neural network for aspect levelsentiment classification. Our approach models aspects and sentences in a jointway and explicitly captures the interaction between aspects and contextsentences. With the AOA module, our model jointly learns the representationsfor aspects and sentences, and automatically focuses on the important parts insentences. Our experiments on laptop and restaurant datasets demonstrate ourapproach outperforms previous LSTM-based architectures.

Aspect Level Sentiment Classification with Attention-over-Attention Neural Networks