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DiffSBR: A diffusion model for session-based recommendation
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DOI：10.1016/j.ipm.2025.104284.png)
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Abstract
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• This study addresses the issue of homogeneous and heterogeneous preferences in SBR. • Combining Transformer and hypergraph convolution for local and global modeling. • Cluster-aware diffusion model effectively represents preference as distribution. • Experimental results demonstrate DiffSBR’s superior recommendation performance.
Keywords:
Session-based recommendation
Diffusion model
Graph neural network
User preference modeling
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