Abstractive Summarization of Product Reviews Using Discourse Structure
Shima Gerani, Yashar Mehdad, Giuseppe Carenini, Raymond T. Ng, Bita Nejat · 2014
We propose a novel abstractive summarization system for product reviews by taking advantage of their discourse structure.First, we apply a discourse parser to each review and obtain a discourse tree representation for every review.We then modify the discourse trees such that every leaf node only contains the aspect words.Second, we aggregate the aspect discourse trees and generate a graph.We then select a subgraph representing the most important aspects and the rhetorical relations between them using a PageRank algorithm, and transform the selected subgraph into an aspect tree.Finally, we generate a natural language summary by applying a template-based NLG framework.Quantitative and qualitative analysis of the results, based on two user studies, show that our approach significantly outperforms extractive and abstractive baselines.