端到端方面级情感分析综述

Survey on End-to-end Aspect-based Sentiment Analysis

方面级情感分析作为一种重要的细粒度情感分析任务,旨在从方面层面分析和理解用户的观点,近年来受到学术界和工业界的广泛关注.端到端方面级情感分析是方面级情感分析的一个重要分支,目的是同时提取方面术语并确定其情感极性.然而,目前尚缺乏单独对其现有方法的系统分类和性能比较的综述文章.针对这一现状,本文首先概述了方面级情感分析任务的定义及相关研究,并归纳了该领域现有数据集的情况.在此基础上,本文分别对不同类型的端到端方面级情感分析方法进行了归纳和总结,并进一步通过不同数据集上的对比介绍了不同方法的性能.最后,本文针对现有方法的发展进行了总结,归纳了当前研究仍然面临的挑战,并指出了未来研究可能的方向.

Aspect-based sentiment analysis,as an important task of fine-grained sentiment analysis,aims to analyze and understand user′s perspectives at the aspect level,and has received extensive attention from the academic and industrial communities in recent years.End-to-end aspect-based sentiment analysis is a crucial branch of aspect-based sentiment analysis,which aims to simultaneously extract aspect terms and determine their sentiment polarity.However,there is a lack of comprehensive review articles that systematically classify and compare existing methods for this task.In view of this situation,this paper first provides an overview of the definition and related research of aspect-based sentiment analysis,and summarizes the existing datasets in this field.Based on this foundation,this paper categorizes and summarizes different types of end-to-end aspect-based sentiment analysis methods,and further introduces their performance through comparisons on different datasets.Finally,this paper concludes the development of existing methods,summarizes the challenges still faced by current research,and identifies potential directions for future research.