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Raghad Al-Shabandar
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2020 – today
- 2023
- [c9]Ahmed Mohamed Abdou Ahmed, Abdulaziz Al-Nahari, Raghad Al-Shabandar, Chong Kim Loy, A. H. Mohammed:
Telecom Customer Experience Analysis Using Sentiment Analysis and Natural Language Processing - Comparative Study. DaSET 2023: 169-180 - [c8]Saurabh Gupta, Raghad Al-Shabandar, Chong Kim Loy, Ammar H. Mohammed:
Multivariate Comparative Analysis of Statistical and Deep Learning Models for Prediction Hardware Failure. DaSET 2023: 291-299 - [c7]Raghad Al-Shabandar, Ali Jaddoa, A. H. Mohammed, Abir Jaafar Hussain:
Intelligent Measuring for a Customer Satisfaction Level Inspired by Transformation Language Model. DeSE 2023: 706-712 - [c6]Raghad Al-Shabandar, Ali Jaddoa, Abir Hussain:
A Risk Model for Assessing Exposure Factors Influence Oil Price Fluctuations. ICIC (5) 2023: 482-492 - 2020
- [j3]Zaynab Ahmed, Abir Jaafar Hussain, Wasiq Khan, Thar Baker, Haya Al-Askar, Janet Lunn, Raghad Al-Shabandar, Dhiya Al-Jumeily, Panos Liatsis:
Lossy and Lossless Video Frame Compression: A Novel Approach for High-Temporal Video Data Analytics. Remote. Sens. 12(6): 1004 (2020) - [c5]Raghad Al-Shabandar, Abir Hussain, Robert Keight, Wasiq Khan:
Students Performance Prediction in Online Courses Using Machine Learning Algorithms. IJCNN 2020: 1-7
2010 – 2019
- 2019
- [b1]Raghad Al-Shabandar:
The application of machine learning for early detection of at-risk learners in Massive Open Online Courses. Liverpool John Moores University, UK, 2019 - [j2]Raghad Al-Shabandar, Abir Jaafar Hussain, Panos Liatsis, Robert Keight:
Detecting At-Risk Students With Early Interventions Using Machine Learning Techniques. IEEE Access 7: 149464-149478 (2019) - [c4]Raghad Al-Shabandar, Gaye Lightbody, Fiona Browne, Jun Liu, Haiying Wang, Huiru Zheng:
The Application of Artificial Intelligence in Financial Compliance Management. AIAM (ACM) 2019: 8:1-8:6 - 2018
- [j1]Raghad Al-Shabandar, Abir Jaafar Hussain, Panos Liatsis, Robert Keight:
Analyzing Learners Behavior in MOOCs: An Examination of Performance and Motivation Using a Data-Driven Approach. IEEE Access 6: 73669-73685 (2018) - [c3]Raghad Al-Shabandar, Abir Hussain, Robert Keight, Andy Laws, Thar Baker:
The Application of Gaussian Mixture Models for the Identification of At-Risk Learners in Massive Open Online Courses. CEC 2018: 1-8 - 2017
- [c2]Raghad Al-Shabandar, Abir Hussain, Andy Laws, Robert Keight, Janet Lunn:
Towards the Differentiation of Initial and Final Retention in Massive Open Online Courses. ICIC (1) 2017: 26-36 - [c1]Raghad Al-Shabandar, Abir Hussain, Andy Laws, Robert Keight, Janet Lunn, Naeem Radi:
Machine learning approaches to predict learning outcomes in Massive open online courses. IJCNN 2017: 713-720
Coauthor Index
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