Aspect-Based Sentiment Analysis Methods in Recent Years

Zohre Madhoushi, A. Hamdan, S. Zainudin
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引用次数: 17

Abstract

Sentiment Analysis (SA) is the computational treatment of opinions, sentiments and subjectivity of text. Aspect-based Sentiment Analysis (ABSA) is a specific SA that aims to extract most important aspects of an entity and predict the polarity of each aspect from the text. A review of the recent state-of-the-art in ABSA, shows the remarkable growing in finding both aspect, and the corresponding sentiment. Current methods are categorized based on their proposed algorithms and models. For each discussed study, aspect extraction method and sentiment prediction method, the dataset, domain and the reported performance is included. The main goal of this work is to review ABSA techniques with brief details. The main contributions of this paper consist of the refined categorizations of a great number of recent articles, comparing them and the illustration of the recent trend of research in the ABSA.
近年来基于方面的情感分析方法
情感分析是对文本的观点、情感和主观性进行计算处理的一种方法。基于方面的情感分析(ABSA)是一种特定的情感分析,旨在提取实体的最重要方面,并从文本中预测每个方面的极性。回顾ABSA最近的最新技术,发现这两个方面的显著增长,以及相应的情绪。目前的方法是根据其提出的算法和模型进行分类的。对于每个讨论的研究,方面提取方法和情绪预测方法,包括数据集,领域和报告性能。这项工作的主要目的是回顾ABSA技术的简要细节。本文的主要贡献包括对大量最近的文章进行了精细化的分类,对它们进行了比较,并对ABSA的最新研究趋势进行了说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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