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Node Recommendation on E-comm2

Node Recommendation on E-comm2

0.333Hits@1P2GNN

Updated 7mo ago

Evaluation results

Method	Links
P2GNN2026.03		0.333	0.782	1.09	1.568	0.657
GCN2026.03		0.285	0.753	1.056	1.531	0.613

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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