BERT-Based Sentiment Analysis for Low-Resourced Languages: A Case Study of Urdu Language-Reference-Cited by-同舟云学术

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BERT-Based Sentiment Analysis for Low-Resourced Languages: A Case Study of Urdu Language

Published:2023 Issue: Volume:11 Page:110245-110259
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ashraf Muhammad Rehan¹,Jana Yasmeen²,Umer Qasim²^ORCID,Jaffar M. Arfan¹,Chung Sungwook³^ORCID,Ramay Waheed Yousuf⁴^ORCID

Affiliation:

1. Department of Computer Science, Superior University, Lahore, Pakistan

2. Department of Computer Sciences, COMSATS University Islamabad, Vehari, Pakistan

3. Department of Computer Engineering, Changwon National University, Changwon, South Korea

4. Department of Computer Science, Air University, Multan, Pakistan

Funder

Korea Meteorological Administration Research and Development Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10271297.pdf?arnumber=10271297

Reference58 articles.

1. Lexical Variation and Sentiment Analysis of Roman Urdu Sentences with Deep Neural Networks

2. Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI

3. Sentiment Analysis in E-commerce Using SVM on Roman Urdu Text

4. Identifying SNAREs by Incorporating Deep Learning Architecture and Amino Acid Embedding Representation

5. Multi-class sentiment analysis of urdu text using multilingual BERT

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Transforming Language Translation: A Deep Learning Approach to Urdu–English Translation;Journal of Ambient Intelligence and Humanized Computing;2024-08-22

2. Advancing Urdu NLP: Aspect-Based Sentiment Analysis with Graph Attention Networks;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. Sentiment Analysis in Low-Resource Settings: A Comprehensive Review of Approaches, Languages, and Data Sources;IEEE Access;2024

4. Sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning;Computers, Materials & Continua;2024

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