Neural Network-Based Abstract Generation for Opinions and Arguments

@inproceedings{Wang2016NeuralNA,
  title={Neural Network-Based Abstract Generation for Opinions and Arguments},
  author={Lu Wang and Wang Ling},
  booktitle={HLT-NAACL},
  year={2016}
}
We study the problem of generating abstractive summaries for opinionated text. We propose an attention-based neural network model that is able to absorb information from multiple text units to construct informative, concise, and fluent summaries. An importance-based sampling method is designed to allow the encoder to integrate information from an important subset of input. Automatic evaluation indicates that our system outperforms state-ofthe-art abstractive and extractive summarization systems… CONTINUE READING
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