Deep Learning Approach for Aspect-Based Sentiment Classification: A Comparative Review

被引:22
|
作者
Trisna, Komang Wahyu [1 ,2 ]
Jie, Huang Jin [1 ,3 ]
机构
[1] Harbin Univ Sci & Technol, Sch Comp Sci & Technol, Harbin 150080, Peoples R China
[2] STMIK Primakara, Dept Informat, Bali, Indonesia
[3] Harbin Univ Sci & Technol, Key Lab Adv Mfg & Intelligent Technol, Harbin, Peoples R China
关键词
ASPECT EXTRACTION; MODEL; NETWORK;
D O I
10.1080/08839514.2021.2014186
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The emergence of various e-commerce sites has led to an increase in review sites for various services and products. People nowadays easily get information about products and services that will be used through reviews. Here sentiment analysis plays an important role in classifying the polarity of product reviews. However, with a large number of reviews, a sentiment analysis that only gives overall polarity is not sufficient. This will make it difficult to find the reviews of certain aspects (features) of the product. Aspect-based sentiment analysis as fine-grained sentiment analysis is able to provide specific polarity for each aspect contained in a sentence. Various kinds of development methods have been carried out to provide accurate results in aspect-based sentiment analysis. This paper will discuss the various deep learning methods that have been carried out and provide the possibility of research that can be carried out from Aspect-Based Sentiment Analysis.
引用
收藏
页数:37
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