A data package for abstractive opinion summarization, title generation, and rating-based sentiment prediction for airline reviews.

ABSTRACT: Customer reviews are valuable resources containing customer opinions and sentiments toward the product. The reviews are informative but can be quite lengthy or may contain repetitive information calling for opinion summarization systems that retain only the significant opinion information from the review. Abstractive summarization is a form of text summarization that generates a summary mimicking a human-written summary [1]. When pretrained language models are finetuned for abstractive review summarization, there usually occurs a problem known as the 'domain shift', because the source and target domains exhibit data from varying distributions [2]. This issue results in performance degradation of the model at the target end. This paper contributes a data package comprising of an annotated a

SUBMITTER: Syed AA 

PROVIDER: S-EPMC10504493 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature