Apr 11, 2024 · We propose the Multi-Scenario Causal-driven Adaptive Network M-scan. This model incorporates a Scenario-Aware Co-Attention mechanism that explicitly extracts ...

May 13, 2024 · We propose the Multi-Scenario Causal-driven Adaptive Network M-scan. This model incorporates a Scenario-Aware Co-Attention mechanism that explicitly extracts ...

May 22, 2024 · The model addresses key challenges in multi-scenario recommendation systems, such as data sparsity in some scenarios and bias due to direct ...

These recommendation algorithms rely on users' historical behavior data to train recommendation models that predict whether users will click on or like specific ...

This model incorporates a Scenario-Aware Co-Attention mechanism that explicitly extracts user interests from other scenarios that align with the current ...

Oct 24, 2024 · Request PDF | On May 13, 2024, Jiachen Zhu and others published M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation ...

Mar 18, 2024 · "M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation Jiachen Zhu, Yichao Wang, Jianghao Lin, Jiarui Qin, Ruiming Tang ...

May 13, 2024 · M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation ... We primarily focus on the field of multi-scenario recommendation ...

M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation · no code implementations • 11 Apr 2024 • Jiachen Zhu, Yichao Wang, Jianghao Lin ...

Co-authors ; M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation. J Zhu, Y Wang, J Lin, J Qin, R Tang, W Zhang, Y Yu. Proceedings of the ...