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MS-HGAT: Memory-Enhanced Sequential Hypergraph Attention Network for Information Diffusion Prediction

AAAI 2022 · Image generation › Fast diffusion sampling · approach: Diffusion models as perception tools · 80 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
combine friendship and diffusion-interaction relations using sequential hypergraphs, memory, and gated fusionMS-HGAT · Twitter, Douban, Android, ChristianityHits@100: 52.19 -> 58.91; 39.71 -> 42.75; 24.08 -> 27.55; 52.47 -> 55.62Helped
combine friendship and diffusion-interaction relations using sequential hypergraphs, memory, and gated fusionMS-HGAT · Twitter, Douban, Android, ChristianityMAP@100: 21.75 -> 23.30; 12.28 -> 12.60; 6.50 -> 6.96; 16.44 -> 18.40Helped
add friendship-graph information (ablation)MS-HGAT · TwitterHits@100: 57.20 -> 58.91Helped
add friendship-graph information (ablation)MS-HGAT · TwitterMAP@100: 21.38 -> 23.30Helped
add diffusion hypergraphs (ablation)MS-HGAT · TwitterHits@100: 57.41 -> 58.91Helped
add diffusion hypergraphs (ablation)MS-HGAT · TwitterMAP@100: 22.24 -> 23.30Helped
add user memory (ablation)MS-HGAT · TwitterHits@100: 58.63 -> 58.91Helped
add user memory (ablation)MS-HGAT · TwitterMAP@100: 22.74 -> 23.30Helped
add cascade memory (ablation)MS-HGAT · TwitterHits@100: 58.32 -> 58.91Helped
add cascade memory (ablation)MS-HGAT · TwitterMAP@100: 21.96 -> 23.30Helped
add HGAT attention mechanism (ablation)MS-HGAT · TwitterHits@100: 58.95 -> 58.91Mixed
add HGAT attention mechanism (ablation)MS-HGAT · TwitterMAP@100: 22.76 -> 23.30Helped

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