activity
20192026
most citedCustomer churn prediction in telecom using machine learning and social network analysis in big data platform

423 citations · 467 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CR2026

Context-Aware Web Attack Detection in Open-Source SIEM Systems via MITRE ATT&CK-Enriched Behavioral Profiling

Badr Alboushy, Assef Jafar, Mohamad Aljnidi +2

Security Information and Event Management (SIEM) systems aggregate log data from heterogeneous sources to detect coordinated attacks. Traditional rule-based correlation engines str…

cs.SD2024★ 1 cited

Study of the Performance of CEEMDAN in Underdetermined Speech Separation

Rawad Melhem, Riad Hamadeh, Assef Jafar

The CEEMDAN algorithm is one of the modern methods used in the analysis of non-stationary signals. This research presents a study of the effectiveness of this method in audio sourc…

cs.SD2024

Developing an Effective Training Dataset to Enhance the Performance of AI-based Speaker Separation Systems

Rawad Melhem, Assef Jafar, Oumayma Al Dakkak

This paper addresses the challenge of speaker separation, which remains an active research topic despite the promising results achieved in recent years. These results, however, oft…

cs.SD2023

Improving Deep Attractor Network by BGRU and GMM for Speech Separation

Rawad Melhem, Assef Jafar, Riad Hamadeh

Deep Attractor Network (DANet) is the state-of-the-art technique in speech separation field, which uses Bidirectional Long Short-Term Memory (BLSTM), but the complexity of the DANe…

cs.SD2023★ 1 cited

Towards Solving Cocktail-Party: The First Method to Build a Realistic Dataset with Ground Truths for Speech Separation

Rawad Melhem, Assef Jafar, Oumayma Al Dakkak

Speech separation is very important in real-world applications such as human-machine interaction, hearing aids devices, and automatic meeting transcription. In recent years, a sign…

cs.CY2019★ 423 cited

Customer churn prediction in telecom using machine learning and social network analysis in big data platform

Abdelrahim Kasem Ahmad, Assef Jafar, Kadan Aljoumaa

Customer churn is a major problem and one of the most important concerns for large companies. Due to the direct effect on the revenues of the companies, especially in the telecom f…

cs.LG2019★ 42 cited

Predicting customer's gender and age depending on mobile phone data

Ibrahim Mousa AlZuabi, Assef Jafar, Kadan Aljoumaa

In the age of data driven solution, the customer demographic attributes, such as gender and age, play a core role that may enable companies to enhance the offers of their services…