The contributions of this work are three-fold: • We propose a novel unsupervised end-to-end model to generate an abstractive summary of a single product review while inducing a latent discourse tree • The experimental results demonstrate that our model is competitive with or outperforms other unsupervised models.
for long reviews, it achieves a competitive or better performance than the supervised models.