Recognizing themes in Amazon reviews through Unsupervised Multi-Document Summarization

Jeff Chen, Hanoz Bhathena, William Locke

Abstract

We propose a system for unsupervised extractive summarization using Deep Learning feature extractors combined with several different models: k-means, affinity propagation, DBSCAN, and PageRank. We also propose a system for unsupervised abstractive summarization using a Deep Learning model. These summarization models capture the major themes in all the reviews of a product and optionally report the number of users who mentioned the same theme, hence giving shoppers a sense of salience.