RoBERTaNET: Enhanced RoBERTa Transformer Based Model for Cyberbullying Detection With GloVe Features

Autor: Arwa A. Jamjoom, Hanen Karamti, Muhammad Umer, Shtwai Alsubai, Tai-Hoon Kim, Imran Ashraf

Publikováno v: IEEE Access, Vol 12, Pp 58950-58959 (2024)

Online platforms are fostering social interaction, but unfortunately, this has given rise to antisocial behaviors such as cyberbullying, trolling, and hate speech on a global scale. The detection of hate and aggression has become a vital aspect of co

Externí odkaz: https://doaj.org/article/ecc0a4bc13184eadabece7ce528b4777

The use of knowledge extraction in predicting customer churn in B2B

Autor: Arwa A. Jamjoom

Publikováno v: Journal of Big Data, Vol 8, Iss 1, Pp 1-14 (2021)

Abstract Data mining techniques were used to investigate the use of knowledge extraction in predicting customer churn in insurance companies. Data were included from a health insurance company for providing insight into churn behaviour based on a des

Externí odkaz: https://doaj.org/article/03c6f9e826254212a0b15748e2b4e74c

Real-time DDoS flood attack monitoring and detection (RT-AMD) model for cloud computing.

Autor: Bamasag O; Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia., Alsaeedi A; Department of Computer Science, University of Jeddah, Jeddah, Saudi Arabia., Munshi A; Cybersecurity Department, University of Jeddah, Jeddah, Saudi Arabia., Alghazzawi D; Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia., Alshehri S; Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia., Jamjoom A; Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia.

Publikováno v: PeerJ. Computer science [PeerJ Comput Sci] 2022 Jun 13; Vol. 7, pp. e814. Date of Electronic Publication: 2022 Jun 13 (Print Publication: 2022).

Improving Prediction Accuracy of "Central Line-Associated Blood Stream Infections" Using Data Mining Models.

Autor: Noaman AY; Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia., Nadeem F; Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia., Ragab AHM; Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia., Jamjoom A; Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia., Al-Abdullah N; Clinical Epidemiology & Infection Control, Faculty of Nursing, King Abdulaziz University, Jeddah, Saudi Arabia., Nasir M; Department of Computer Science and Software Engineering, University of Hail, Hail, Saudi Arabia., Ali AG; Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia.

Publikováno v: BioMed research international [Biomed Res Int] 2017; Vol. 2017, pp. 3292849. Date of Electronic Publication: 2017 Sep 20.