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Boumedyen Shannaq

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Open access Sep 2026

Optimizing Arabic Document Representation via Minimal-Term TF-IDF and Co-Occurrence Integration: Empirical Evaluation Across Multiple Classifiers

This study outlines a methodical investigation into optimizing Arabic document representation for classification. It concludes that a balanced selection of minimal terms can achieve high performance while reducing computational load. We conducted experiments on a corpus of 10,000 Arabic news sections from 111,728 docum...

Boumedyen Shannaq · 0 citations
Open access 2026

Self-Supervised Knowledge Representation for Rare Fraud and Operational Failure Detection in Multi-Channel Payment Systems

It is shown that naive, generic, SSL-based anomaly detectors lead to reduced precision, and task-adapted representations of supervised models, stacked with task-adapted representations, can increase fraud recall by up to 4.9 with a small F1 increase, enhancing a knowledge based perspective of when self-supervised repre...

Boumedyen Shannaq, N. Elshaiekh, Basel Bani-Ismail et al. · 0 citations

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