An Investigation of Extraction Method for Evaluation Target Words and Evaluation Words Using Deep Language Model for Aspect-Based Summarization

Abstract

In recent years, machine learning technology has made significant advancements, and it has also been utilized in various tasks in natural language processing. One of these tasks is ”aspect-based summarization,” which involves summarizing information based on the important aspect or viewpoint within a text. In this study, we propose a method for automatically extracting evaluation target words and evaluation terms, which are crucial elements related to the ”aspect,” using a deep language model. We utilize the ”chABSA-dataset” created and released by TIS Corporation as part of aspect-based summarization research and examine the effectiveness of the proposed method through experiments.