Aspect and Opinion Aware Abstractive Review Summarization with Reinforced Hard Typed Decoder

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pp. 2061-2064, 2019.

Cited by: 2|Bibtex|Views39|DOI:https://doi.org/10.1145/3357384.3358142
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Other Links: dl.acm.org|dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

In this paper, we study abstractive review summarization. Observing that review summaries often consist of aspect words, opinion words and context words, we propose a two-stage reinforcement learning approach, which first predicts the output word type from the three types, and then leverages the predicted word type to generate the final w...More

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