Affiliations: Computer Department, Beijing Institute of Petrochemical Technology, Beijing, China
Correspondence:
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Corresponding author. Shibo Zhang, Computer Department, Beijing Institute of Petrochemical Technology, Beijing, China. E-mail: bjshibo@foxmail.com.
Abstract: With the rapid growth of online reviews, the rapid and effective access to summary information is a hot topic of research. In this paper, an abstract sentence extraction model based on hierarchical attention network is proposed. The model has an encoder-decoder structure, which introduces a two-layer attention mechanism. The sentence encoder uses attention mechanism to obtain the vectorized representation of the sentence by inputting the aspect words. The review document encoder uses the attention mechanism to realize the context association of the sentences before and after. When decoding, a sentence output component composed of the GRU network makes the choice whether the sentence should be selected as the candidate sentence. Greedy algorithm is used to eliminate the redundantly result, and then obtains the final summary based on the sentence sorting method. The experiment results show that the proposed model is better than the benchmark model.
