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Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis [article]

Jialong Tang and Ziyao Lu and Jinsong Su and Yubin Ge and Linfeng Song and Le Sun and Jiebo Luo
2019 arXiv   pre-print
In this paper, we propose a progressive self-supervised attention learning approach for neural ASC models, which automatically mines useful attention supervision information from a training corpus to refine  ...  In aspect-level sentiment classification (ASC), it is prevalent to equip dominant neural models with attention mechanisms, for the sake of acquiring the importance of each context word on the given aspect  ...  In this paper, we propose a novel progressive self-supervised attention learning approach for neural ASC models.  ... 
arXiv:1906.01213v3 fatcat:lspxtgbr5va6jbj6ugrps5ffi4

Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis

Jialong Tang, Ziyao Lu, Jinsong Su, Yubin Ge, Linfeng Song, Le Sun, Jiebo Luo
2019 Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics  
Introduction Aspect-level sentiment classification (ASC), as an indispensable task in sentiment analysis, aims at inferring the sentiment polarity of an input sentence in a certain aspect.  ...  In this paper, we propose a novel progressive self-supervised attention learning approach for neural ASC models.  ...  In this paper, we propose a progressive self-supervised attention learning approach for neural ASC models, which automatically mines useful attention supervision information from a training corpus to refine  ... 
doi:10.18653/v1/p19-1053 dblp:conf/acl/TangLSGSSL19 fatcat:7m44gzqdxrbm5hn7b6c7penbtm

Enhanced Aspect-Based Sentiment Analysis Models with Progressive Self-supervised Attention Learning [article]

Jinsong Su, Jialong Tang, Hui Jiang, Ziyao Lu, Yubin Ge, Linfeng Song, Deyi Xiong, Le Sun, Jiebo Luo
2021 arXiv   pre-print
To deal with this issue, we propose a progressive self-supervised attention learning approach for attentional ABSA models.  ...  In aspect-based sentiment analysis (ABSA), many neural models are equipped with an attention mechanism to quantify the contribution of each context word to sentiment prediction.  ...  Progressive Self-supervision for Self-attention within the BERT Intuitively, we can directly apply progressive self-supervised attention learning to enhance the learning of self-attentions within the BERT  ... 
arXiv:2103.03446v1 fatcat:kvqjjjxzx5hdzilbeax2o57sny

Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis

Nan Xu, Wenji Mao, Guandan Chen
2019 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Previous work on aspect-level sentiment analysis is text-based.  ...  As a fundamental task of sentiment analysis, aspect-level sentiment analysis aims to identify the sentiment polarity of a specific aspect in the context.  ...  aspect-level sentiment analysis.  ... 
doi:10.1609/aaai.v33i01.3301371 fatcat:2dee2y5abne77a7iceqkyz6xkq

Sentiment analysis using deep learning approaches: an overview

Olivier Habimana, Yuhua Li, Ruixuan Li, Xiwu Gu, Ge Yu
2019 Science China Information Sciences  
Thus, extensive research has been done for sentiment analysis using machine learning approaches [41] [42] [43] .  ...  Recently, deep learning approaches have been proposed for different sentiment analysis tasks and have achieved state-of-the-art results.  ...  Attention based models with aspect information. Wang et al. [140] designed an attention-based LSTM with aspect embedding (ATAE-LSTM) model for aspect sentiment analysis.  ... 
doi:10.1007/s11432-018-9941-6 fatcat:nbevrfiyybhszirol2af26c6ve

A Review of Text Corpus-Based Tourism Big Data Mining

Qin Li, Shaobo Li, Sen Zhang, Jie Hu, Jianjun Hu
2019 Applied Sciences  
profiles, and make policies for supervising tourism markets.  ...  The successes of these techniques have been further boosted by the progress of natural language processing (NLP), machine learning, and deep learning.  ...  image; market supervision/demand; transfer learning; meta-learning; sentiment aspect; aspect-base sentiment analysis; target-dependent sentiment analysis; NLP; deep learning; machine learning; text representation  ... 
doi:10.3390/app9163300 fatcat:chb3pbtj5jgq7fauniomsb22yu

Interactive Rule Attention Network for Aspect-level Sentiment Analysis

Qiang Lu, Zhenfang Zhu, Dianyuan Zhang, Wenqing Wu, Qiangqiang Guo
2020 IEEE Access  
Therefore, we propose an interactive rule attention network (IRAN) for aspect-level sentiment analysis.  ...  Recent researches show that the finegrained sentiment analysis for aspect-level has become a research hotspot.  ...  MN(+AS) and TNET-ATT(+AS) are improved on the basis of MN and TNET, which propose a progressive self-supervised attention learning approach.  ... 
doi:10.1109/access.2020.2981139 fatcat:xnohfni7vbewnbwxnj2iuurble

Feature Set Selection for Sentiment Analysis

Ganesh K. Shinde
2021 International Journal for Research in Applied Science and Engineering Technology  
Considering that the final decade, Sentiment evaluation has received increased attention from many researchers as a procedure for addressing subject matters, such as the a fore mentioned ones.  ...  Keywords: Sentiment analysis, support vector machine, maximum entropy, with features, without features, artificial intelligence.  ...  Two kinds of learning that usually used in the sentiment analysis, which is supervised learning and unsupervised learning [3] .  ... 
doi:10.22214/ijraset.2021.38511 fatcat:z2xdmhvgcbft5pcswop4gtqd7q

Main Concepts, State of the Art and Future Research Questions in Sentiment Analysis

2015 Acta Polytechnica Hungarica  
at least as effective as supervised learning techniques.  ...  First of all, the fundamental concepts and challenges of the research field known as Sentiment Analysis (SA) are presented.  ...  According to Liu [41] there are commonly three different levels of analysis: Document level; Sentence level; and Entity Feature or Aspect level.  ... 
doi:10.12700/aph.12.3.2015.3.6 fatcat:o5zrfk7mh5bprhjt5ddyxxy6sq

Multiple Interactive Attention Networks for Aspect-Based Sentiment Classification

Dianyuan Zhang, Zhenfang Zh, Qiang Lu, Hongli Pei, Wenqing Wu, Qiangqiang Guo
2020 Applied Sciences  
Aspect-Based (also known as aspect-level) Sentiment Classification (ABSC) aims at determining the sentimental tendency of a particular target in a sentence.  ...  With the successful application of the attention network in multiple fields, attention-based ABSC has aroused great interest.  ...  TNet-ATT proposed a progressive self-supervised attention mechanism algorithm based on TNet-LF.  ... 
doi:10.3390/app10062052 fatcat:32ebt4rslnbkjftmjjie3ropx4

Sentiment Analysis Approaches and Applications: A Survey

Shamsa Umar, Maryam M, Fizza Azhar, Sayyam Malik, Ghulam Samdani
2018 International Journal of Computer Applications  
This situation and trend attract attention towards the research of sentiment analysis. Therefore, sentiment investigation idea is proposed.  ...  Among various applications of Natural Language processing (NLP) and Machine Learning (ML) Sentiment Analysis (SA) is very popular.  ...  Aspect-level sentiment analysis yields exceptionally fine grained sentiment data which can be helpful for applications in different spaces.  ... 
doi:10.5120/ijca2018916630 fatcat:lwap7uwshffx5inaw7yorlyh6i

Aspect-Level Sentiment Analysis Approach via BERT and Aspect Feature Location Model

Guangyao Pang, Keda Lu, Xiaoying Zhu, Jie He, Zhiyi Mo, Zizhen Peng, Baoxing Pu, Zhuojun Duan
2021 Wireless Communications and Mobile Computing  
However, the existing aspect-level sentiment analysis methods mainly focus on attention mechanism and recurrent neural network.  ...  Secondly, for the sake of learning the expression features of aspect words and the interactive information of aspect words' context, we construct an aspect-based sentiment feature extraction method.  ...  This feature allows neural networks to be used for aspect-level sentiment analysis tasks and has attracted the attention of researchers [10, 11] .  ... 
doi:10.1155/2021/5534615 fatcat:3kzuz6cm6jeblcaa4x2fz7ssbi

Comparative Study of Various Approaches, Applications and Classifiers for Sentiment Analysis

Prajval Sudhir, Varun Deshakulkarni Suresh
2021 Global Transitions Proceedings  
Sentiment analysis is contextual mining of text which identifies and extracts subjective information in textual data. sentiment analysis proves to be an incredible asset for users to extract essential  ...  In this paper, the main focus is on the popular NLP task of Sentiment analysis.  ...  A transformer architecture is an encoder-decoder network that uses self-attention on the encoder side and attention on the decoder side.  ... 
doi:10.1016/j.gltp.2021.08.004 fatcat:sktxcdw33fho7juorhmwa7fkrm

Arabic aspect based sentiment classification using BERT [article]

Mohammed M.Abdelgwad
2021 arXiv   pre-print
Aspect-based sentiment analysis(ABSA) is a textual analysis methodology that defines the polarity of opinions on certain aspects related to specific targets.  ...  This article explores the modeling capabilities of contextual embeddings from pre-trained language models, such as BERT, and making use of sentence pair input on Arabic aspect sentiment polarity classification  ...  INSIGHT-1 combined aspect embedding with each word embedding and fed the resulting mixture to CNN for Aspect sentiment analysis (Ruder et al., 2016b) .  ... 
arXiv:2107.13290v3 fatcat:hjkmmmo2y5dstoc64xighnqi2y

A Review on Multi-Lingual Sentiment Analysis by Machine Learning Methods

Santwana Sagnika, School of Computer Engineering, Kalinga Institute of Industrial Technology Deemed to be University, Bhubaneswar, Odisha, India, Anshuman Pattanaik, Bhabani Shankar Prasad Mishra, Saroj K. Meher
2020 Journal of Engineering Science and Technology Review  
This task, known as sentiment analysis, is currently a prominent area of research. Sentiment analysis can be useful for businesses, data analysts and data scientists, as well as customers.  ...  This paper attempts to provide a detailed study on the sentiment analysis methods applied on languages other than English. The tools used, pros and cons, and efficiency of all methods is covered.  ...  [63] implemented an unsupervised mechanism of topic modeling that enabled aspect-level sentiment analysis for any given language.  ... 
doi:10.25103/jestr.132.19 fatcat:aqvglobonjbh3inz3oewnvtdsu
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