An Attempt of Multi-Document Summarization of Product Reviews Using Abstractive Summarization

Abstract

In this study, we propose a method for generating summaries from multiple review documents about products using the deep learning model T5. We conducted transfer learning using our own review summary data based on a single-document summarization model created with the Livedoor News Corpus. We report the evaluation results of the summaries generated by the model after transfer learning.