3 papers
cs.IR2026
MOSAIC: Multi-Domain Orthogonal Session Adaptive Intent Capture for Prescient Recommendations
Abderaouf Bahi, Mourad Boughaba, Ibtissem Gasmi +2
Capturing user intent across heterogeneous behavioral domains stands as a fundamental challenge in session-based recommender systems. Yet, existing multi-domain approaches frequent…
cs.LG2026
FreeGNN: Continual Source-Free Graph Neural Network Adaptation for Renewable Energy Forecasting
Abderaouf Bahi, Amel Ourici, Ibtissem Gasmi +3
Accurate forecasting of renewable energy generation is essential for efficient grid management and sustainable power planning. However, traditional supervised models often require…
cs.IR2026
Benchmarking Deep Neural Networks for Modern Recommendation Systems
Abderaouf Bahi, Inoussa Mouiche, Ibtissem Gasmi
This paper presents a requirement-oriented benchmark of seven deep neural architectures, CNN, RNN, GNN, Autoencoder, Transformer, Neural Collaborative Filtering, and Siamese Networ…