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Multi-behavioral recommendation algorithm based on decoupled graph convolution
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DOI：10.1016/j.eswa.2025.129618.png)
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Abstract
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• Decoupled graph convolution for multi-behavioral recommendation algorithm design. • Divide a multi-behavioral isomorphic graph into multiple non-overlapping ones. • Decoupled graph convolution and contrastive learning to learn feature representation. • Our model outperforms other state-of-the-art methods.
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