MOSAIC: Multi-Domain Orthogonal Session Adaptive Intent Capture for Prescient Recommendations
Capturing user intent across heterogeneous behavioral domains stands as a fundamental challenge in session-based recommender systems. Yet, existing multi-domain approaches frequently fail to isolate the distinct contribution of cross-domain interactions from those arising within individual domains, limiting their ability to build rich and transferable user representations. In this work, we propose MOSAIC, a Multi-Domain Orthogonal Session Adaptive Intent Capture framework that explicitly factorizes user preferences into three orthogonal components: domain-specific, domain-common, and cross-sequence-exclusive representations. Our approach employs a triple-encoder architecture, where each e...
| Authors | Abderaouf Bahi, Mourad Boughaba, Ibtissem Gasmi et al. |
|---|---|
| Primary category | cs.IR |
| Published | 11 April 2026 |
| Last updated at source | 11 April 2026 |
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