Hany Alashwal
Biographic Data
| ID | 8547178 |
|---|---|
| NAME | Hany Alashwal |
| GIVEN NAMES | Hany |
| FAMILY NAME | Alashwal |
| SIGNATURE | ALASHWAL H |
| AFFILIATIONS | United Arab Emirates University |
| ORCID | 0000-0002-5721-5104 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 0 |
A Systematic Literature Review of Student’ Performance Prediction Using Machine Learning Techniques
Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding the student learning environment by exploring and utilizing educational data using machine learning and data mining techniques. Modern academic institutions operate in a highly competitive and complex environment. Analyzing perfo…
Hybrid feature selection approach to identify optimal features of profile metadata to detect social bots in Twitter
The last few years have revealed that social bots in social networks have become more sophisticated in design as they adapt their features to avoid detection systems. The deceptive nature of bots to mimic human users is due to the advancement of artificial intelligence and chatbots, where these bots learn and adjust very quickly. Therefore, finding the optimal features needed to detect them is an area for further investigation. In this paper, we …
No prominent works on this page.
A Systematic Literature Review of Student’ Performance Prediction Using Machine Learning Techniques
Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding the student learning environment by exploring and utilizing educational data using machine learning and data mining techniques. Modern academic institutions operate in a highly competitive and complex environment. Analyzing perfo…
Hybrid feature selection approach to identify optimal features of profile metadata to detect social bots in Twitter
The last few years have revealed that social bots in social networks have become more sophisticated in design as they adapt their features to avoid detection systems. The deceptive nature of bots to mimic human users is due to the advancement of artificial intelligence and chatbots, where these bots learn and adjust very quickly. Therefore, finding the optimal features needed to detect them is an area for further investigation. In this paper, we …
Artificial Intelligence (2 works) · Computer Science (2 works) · Machine learning (2 works) · Artificial Intelligence in Healthcare (1 work) · Artificial neural network (1 work) · COVID-19 diagnosis using AI (1 work) · Data mining (1 work) · Data science (1 work) · Educational Data Mining (1 work) · F1 score (1 work)