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Shaymaa E. Sorour
Shaymaa E. Sorour
Kyushu University, Japan (PhD), Kafrelsheikh Univesity, King Faisal University (Associate Professor)
Verified email at kfu.edu.sa - Homepage
Title
Cited by
Cited by
Year
Comparison of predicting student’s performance using machine learning algorithms
V Vijayalakshmi, K Venkatachalapathy
International Journal of Intelligent Systems and Applications 11 (12), 34, 2019
702019
A predictive model to evaluate student performance
SE Sorour, T Mine, K Goda, S Hirokawa
Journal of Information Processing 23 (2), 192-201, 2015
592015
Predicting Student Grade Based on Free-Style Comments Using Word2Vec and ANN by Considering Prediction Results Obtained in Consecutive Lessons.
J Luo, SE Sorour, K Goda, T Mine
International Educational Data Mining Society, 2015
472015
An efficient data mining technique for assessing satisfaction level with online learning for higher education students during the COVID-19
HE Abdelkader, AG Gad, AA Abohany, SE Sorour
IEEE Access 10, 6286-6303, 2022
462022
Comment data mining to estimate student performance considering consecutive lessons
SE Sorour, K Goda, T Mine
Journal of Educational Technology & Society 20 (1), 73-86, 2017
402017
Predicting students' grades based on free style comments data by artificial neural network
SE Sorour, T Mine, K Goda, S Hirokawa
2014 IEEE Frontiers in Education Conference (FIE) Proceedings, 1-9, 2014
322014
Advanced prediction of performance of a student in an university using machine learning techniques
VU Kumar, A Krishna, P Neelakanteswara, CZ Basha
2020 international conference on electronics and sustainable communication …, 2020
222020
Comments data mining for evaluating student's performance
SE Sorour, T Mine, K Godaz, S Hirokawax
2014 IIAI 3rd International Conference on Advanced Applied Informatics, 25-30, 2014
222014
Estimation of student performance by considering consecutive lessons
SE Sorour, K Goda, T Mine
2015 IIAI 4th International Congress on Advanced Applied Informatics, 121-126, 2015
202015
Correlation of topic model and student grades using comment data mining
S Sorour, K Goda, T Mine
Proceedings of the 46th ACM technical symposium on computer science …, 2015
192015
Building an interpretable model of predicting student performance using comment data mining
SE Sorour, T Mine
2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI …, 2016
182016
Evaluation of effectiveness of time-series comments by using machine learning techniques
SE Sorour, K Goda, T Mine
Journal of information processing 23 (6), 784-794, 2015
182015
A Hybrid Virtual Cloud Learning Model During the COVID-19 Pandemic
HE Sorour, shaymaa E., Tamer M. Kamel
Computers, Materials and Continua, 2021
152021
Study on the influencing factors of the flexibility of university IT management in Education 4.0
Wasilah, LE Nugroho, PI Santosa, SE Sorour
International Journal of Innovation and Learning 30 (2), 132-153, 2021
142021
Correlation of grade prediction performance with characteristics of lesson subject
SE Sorour, J Luo, K Goda, T Mine
2015 IEEE 15th International Conference on Advanced Learning Technologies …, 2015
132015
Efficiency of LSA and K-means in predicting students' Academic performance based on their comments data
SE Sorour, T Mine, K Goda, S Hirokawa
Proceedings of the 6th international conference on computer supported …, 2014
132014
Predict student performance by utilizing data mining technique and support vector machine
A Kadambande, S Thakur, A Mohol, AM Ingole
International Research Journal of Engineering and Technology 4, 2818-2821, 2017
92017
Student performance estimation based on topic models considering a range of lessons
SE Sorour, K Goda, T Mine
Artificial Intelligence in Education: 17th International Conference, AIED …, 2015
92015
Comment data mining for student grade prediction considering differences in data for two classes
合田和正
Journal of Computer & Information Science 15, 12-25, 2014
92014
AFND: Arabic fake news detection with an ensemble deep CNN-LSTM model
SE Sorour, HE Abdelkader
J. Theor. Appl. Inf. Technol 100 (14), 5072-5086, 2022
82022
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