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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

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

A Review of Text Corpus-Based Tourism Big Data Mining

Qin Li, Shaobo Li, Sen Zhang, Jie Hu, Jianjun Hu
2019 Applied Sciences  
The successes of these techniques have been further boosted by the progress of natural language processing (NLP), machine learning, and deep learning.  ...  We summarize and discuss different text representation strategies, text-based NLP techniques for topic extraction, text classification, sentiment analysis, and text clustering in the context of tourism  ...  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

Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis

Nan Xu, Wenji Mao, Guandan Chen
Previous work on aspect-level sentiment analysis is text-based.  ...  Our model includes two interactive memory networks to supervise the textual and visual information with the given aspect, and learns not only the interactive influences between cross-modality data but  ...  With the development of deep learning technologies, some neural network based models have been proposed for multimodal sentiment analysis, achieving significant progress.  ... 
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  
Suggestions include the use of bidirectional encoder representations from transformers (BERT), sentiment-specific word embedding models, cognition-based attention models, common sense knowledge, reinforcement  ...  Therefore, machine learning approaches are preferred for sentiment analysis due to their capacity for dealing with large amounts of data compared with lexicon based approaches [39] .  ...  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

Interactive Rule Attention Network for Aspect-level Sentiment Analysis

Qiang Lu, Zhenfang Zhu, Dianyuan Zhang, Wenqing Wu, Qiangqiang Guo
2020 IEEE Access  
INDEX TERMS Aspect-level sentiment analysis, grammatical rules, IRAN, interaction attention network.  ...  Therefore, we propose an interactive rule attention network (IRAN) for aspect-level sentiment analysis.  ...  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

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

Improving BERT with Self-Supervised Attention [article]

Xiaoyu Kou, Yaming Yang, Yujing Wang, Ce Zhang, Yiren Chen, Yunhai Tong, Yan Zhang, Jing Bai
2020 arXiv   pre-print
In this paper, we propose a novel technique, called Self-Supervised Attention (SSA) to help facilitate this generalization challenge.  ...  Empirically, on a variety of public datasets, we illustrate significant performance improvement using our SSA-enhanced BERT model.  ...  Conclusions and Future Work In this paper, we propose a novel technique called self-supervised attention (SSA) to prevent BERT from overfitting when fine-tuned on small datasets.  ... 
arXiv:2004.03808v3 fatcat:vfdl33hoind2rf7a266optpqi4

Study on Relationship Between Network Public Opinion and New Function Mode of Ideological Education Based on Equations of Mathematical Physics [chapter]

Dongchao Jia, Linlin Li
2013 Lecture Notes in Electrical Engineering  
With the rapid progress and development of network and information technology, the network of public opinion monitoring and management technology is constantly being improved and advanced.  ...  the focus of attention.  ...  The chart reflects that students participate in the network public sentiment, the freshman and senior's attention and thinking analysis ability is not enough or is not taken into consideration.  ... 
doi:10.1007/978-3-642-35419-9_2 fatcat:wca7qmkzfngrtifctiiba23qc4

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  
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.  ...  However, the existing aspect-level sentiment analysis methods mainly focus on attention mechanism and recurrent neural network.  ...  ( x ) x AEN-BERT [30] is a model based on attention mechanism and BERT and shows good performance in aspect-based sentiment analysis tasks (xi) BERT-base is an aspect-based sentiment analysis model  ... 
doi:10.1155/2021/5534615 fatcat:3kzuz6cm6jeblcaa4x2fz7ssbi

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  ...  aspect sentiment classification task. • A simple BERT based model with a linear classification layer was proposed to solve aspect sentiment polarity classification task.  ... 
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.  ...  [36] developed a Cross-Lingual Joint Aspect Sentiment model that simultaneously checks aspect-based opinion expression in both languages.  ... 
doi:10.25103/jestr.132.19 fatcat:aqvglobonjbh3inz3oewnvtdsu

AB-LaBSE: Uyghur Sentiment Analysis via the Pre-Training Model with BiLSTM

Yijie Pei, Siqi Chen, Zunwang Ke, Wushour Silamu, Qinglang Guo
2022 Applied Sciences  
In this paper, we present an effective solution to providing a meaningful and easy-to-use feature extractor for sentiment analysis tasks: using the pre-trained language model with BiLSTM layer.  ...  We close with an overview of the resources for sentiment analysis tasks and some of the open research questions.  ...  Li [14] proposed a new direction-based sentiment analysis method, GBCN, which uses a gating mechanism with an up-down file aspect embedding to enhance and control the BERT representation of aspect-oriented  ... 
doi:10.3390/app12031182 fatcat:uqqj7bs52fhrpinkv7elssszdq

Fine-tuning Pre-trained Contextual Embeddings for Citation Content Analysis in Scholarly Publication [article]

Haihua Chen, Huyen Nguyen
2020 arXiv   pre-print
Citation function and citation sentiment are two essential aspects of citation content analysis (CCA), which are useful for influence analysis, the recommendation of scientific publications.  ...  Our method can be used to enhance the influence analysis of scholars and scholarly publications.  ...  For BERT, we use the BERT-base model with a hidden size of 768, 12 layers and 12 self-attention heads [17] . For XLNet, we also use XLNet-base model with 12 layers, 768 hiddens, 12 heads.  ... 
arXiv:2009.05836v1 fatcat:3rgkzlblencs7lj4csspfplevi
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