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Sentiment Analysis of Product Reviews Using Transformer Enhanced 1D-CNN and BiLSTM Cover

Sentiment Analysis of Product Reviews Using Transformer Enhanced 1D-CNN and BiLSTM

Cybernetics and Information Technologies
Volume 24 (2024): Issue 3 (September 2024)
By: Muhammad Rizwan Rashid Rana,  Asif Nawaz,  Tariq Ali,  Ahmed Saleh Alattas and  Diaa Salama AbdElminaam  
Open Access
|Sep 2024

Authors

Muhammad Rizwan Rashid Rana

rizwanrana315@gmail.com

University Institute of Information Technology, PMAS Arid Agriculture University, Rawalpindi, Pakistan

Asif Nawaz

asif.nawaz@uaar.edu.pk

University Institute of Information Technology, PMAS Arid Agriculture University, Rawalpindi, Pakistan

Tariq Ali

tariq.ali@uaar.edu.pk

University Institute of Information Technology, PMAS Arid Agriculture University, Rawalpindi, Pakistan

Ahmed Saleh Alattas

aalatas@kau.edu.sa

Information Science Department, Faculty of Arts & Humanities, King Abdul-Aziz University, Jeddah, Saudi Arabia

Diaa Salama AbdElminaam

diaa.salama@miuegypt.edu.eg

MEU Research Unit, Middle East University, Amman, Jordan
Jadara Research Center, Jadara University, Irbid, Jordan
DOI: https://doi.org/10.2478/cait-2024-0028 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
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Language: English
Page range: 112 - 131
Submitted on: Apr 16, 2024
|
Accepted on: Aug 15, 2024
|
Published on: Sep 19, 2024
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Sentiment analysis,
Deep learning,
e-Commerce,
Products reviews,
Opinion mining
Related subjects:
Computer sciences,
Information technology

© 2024 Muhammad Rizwan Rashid Rana, Asif Nawaz, Tariq Ali, Ahmed Saleh Alattas, Diaa Salama AbdElminaam, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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