Aspect-Based Sentiment Analysis in Hindi Language by Ensembling Pre-Trained mBERT Models

Sentiment Analysis is becoming an essential task for academics, as well as for commercial companies. However, most current approaches only identify the overall polarity of a sentence, instead of the polarity of each aspect mentioned in the sentence. Aspect-Based Sentiment Analysis (ABSA) identifies...

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Autores principales:	Abhilash Pathak, Sudhanshu Kumar, Partha Pratim Roy, Byung-Gyu Kim
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	aspect-based sentiment analysis BERT classification ensemble Hindi Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/f31531bbf9094a2ab04c2351944bae2e
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id	oai:doaj.org-article:f31531bbf9094a2ab04c2351944bae2e
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spelling	oai:doaj.org-article:f31531bbf9094a2ab04c2351944bae2e2021-11-11T15:39:03ZAspect-Based Sentiment Analysis in Hindi Language by Ensembling Pre-Trained mBERT Models10.3390/electronics102126412079-9292https://doaj.org/article/f31531bbf9094a2ab04c2351944bae2e2021-10-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/21/2641https://doaj.org/toc/2079-9292Sentiment Analysis is becoming an essential task for academics, as well as for commercial companies. However, most current approaches only identify the overall polarity of a sentence, instead of the polarity of each aspect mentioned in the sentence. Aspect-Based Sentiment Analysis (ABSA) identifies the aspects within the given sentence, and the sentiment that was expressed for each aspect. Recently, the use of pre-trained models such as BERT has achieved state-of-the-art results in the field of natural language processing. In this paper, we propose two ensemble models based on multilingual-BERT, namely, <i>mBERT-E-MV</i> and <i>mBERT-E-AS</i>. Using different methods, we construct an auxiliary sentence from this aspect and convert the ABSA problem to a sentence-pair classification task. We then fine-tune different pre-trained BERT models and ensemble them for a final prediction based on the proposed model; we achieve new, state-of-the-art results for datasets belonging to different domains in the Hindi language.Abhilash PathakSudhanshu KumarPartha Pratim RoyByung-Gyu KimMDPI AGarticleaspect-based sentiment analysisBERTclassificationensembleHindiElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2641, p 2641 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	aspect-based sentiment analysis BERT classification ensemble Hindi Electronics TK7800-8360
spellingShingle	aspect-based sentiment analysis BERT classification ensemble Hindi Electronics TK7800-8360 Abhilash Pathak Sudhanshu Kumar Partha Pratim Roy Byung-Gyu Kim Aspect-Based Sentiment Analysis in Hindi Language by Ensembling Pre-Trained mBERT Models
description	Sentiment Analysis is becoming an essential task for academics, as well as for commercial companies. However, most current approaches only identify the overall polarity of a sentence, instead of the polarity of each aspect mentioned in the sentence. Aspect-Based Sentiment Analysis (ABSA) identifies the aspects within the given sentence, and the sentiment that was expressed for each aspect. Recently, the use of pre-trained models such as BERT has achieved state-of-the-art results in the field of natural language processing. In this paper, we propose two ensemble models based on multilingual-BERT, namely, <i>mBERT-E-MV</i> and <i>mBERT-E-AS</i>. Using different methods, we construct an auxiliary sentence from this aspect and convert the ABSA problem to a sentence-pair classification task. We then fine-tune different pre-trained BERT models and ensemble them for a final prediction based on the proposed model; we achieve new, state-of-the-art results for datasets belonging to different domains in the Hindi language.
format	article
author	Abhilash Pathak Sudhanshu Kumar Partha Pratim Roy Byung-Gyu Kim
author_facet	Abhilash Pathak Sudhanshu Kumar Partha Pratim Roy Byung-Gyu Kim
author_sort	Abhilash Pathak
title	Aspect-Based Sentiment Analysis in Hindi Language by Ensembling Pre-Trained mBERT Models
title_short	Aspect-Based Sentiment Analysis in Hindi Language by Ensembling Pre-Trained mBERT Models
title_full	Aspect-Based Sentiment Analysis in Hindi Language by Ensembling Pre-Trained mBERT Models
title_fullStr	Aspect-Based Sentiment Analysis in Hindi Language by Ensembling Pre-Trained mBERT Models
title_full_unstemmed	Aspect-Based Sentiment Analysis in Hindi Language by Ensembling Pre-Trained mBERT Models
title_sort	aspect-based sentiment analysis in hindi language by ensembling pre-trained mbert models
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/f31531bbf9094a2ab04c2351944bae2e
work_keys_str_mv	AT abhilashpathak aspectbasedsentimentanalysisinhindilanguagebyensemblingpretrainedmbertmodels AT sudhanshukumar aspectbasedsentimentanalysisinhindilanguagebyensemblingpretrainedmbertmodels AT parthapratimroy aspectbasedsentimentanalysisinhindilanguagebyensemblingpretrainedmbertmodels AT byunggyukim aspectbasedsentimentanalysisinhindilanguagebyensemblingpretrainedmbertmodels
_version_	1718434707024117760

Aspect-Based Sentiment Analysis in Hindi Language by Ensembling Pre-Trained mBERT Models

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