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Node Recommendation on E-comm 1

Node Recommendation on E-comm 1

3.93Hits@1P2GNN

Updated 7mo ago

Evaluation results

Method	Links
P2GNN2026.03		3.93	3.95	3.96	3.96	3.94
GCN2026.03		3.77	3.81	3.81	3.81	3.79

State-of-the-art paper

P2GNN

$P^2$GNN: Two Prototype Sets to boost GNN Performance

Dataset

E-comm

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Related benchmarks

Node Classification on Squirrel (60/20/20)Node Classification on Film (48%/32%/20% split)Node Classification on Squirrel (48%/32%/20%)Node Classification on Cora (48%/32%/20%)Node Classification on snap-patents (Accuracy and Avg. Rank)

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