Research map / Graph learning / Knowledge and temporal graphs
Ranking Users in Social Networks With Higher-Order Structures
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add motif-based adjacency (M7) to edge-based PageRank | PageRank · DBLP top-10 | NDCG: 0.9464 -> 0.9920 | Helped |
| add motif-based adjacency (M6) to edge-based PageRank | PageRank · Epinions top-10 | NDCG: 0.9777 -> 0.9957 | Helped |
| add motif-based adjacency (M2) to edge-based PageRank | PageRank · Ciao top-10 | NDCG: 0.8332 -> 0.9905 | Helped |
| weight edges by interaction frequency (WPR) instead of binary | PageRank · DBLP/Epinions/Ciao | NDCG: 0.9464 -> 0.9154 (DBLP top-10); identical on Epinions/Ciao | No clear effect |
| choose motif M1 instead of M7 when augmenting PageRank (ablation) | MPR · Ciao top-10 | NDCG: 0.9802 (M1) vs 0.9514 (M7) | Mixed |
| choose motif M6 on DBLP top-10 instead of M7 (ablation) | MPR · DBLP top-10 | NDCG: 0.9920 -> 0.9634 | Hurt |
| mix edge and motif relations (alpha in (0,1)) instead of motif only or edge only (ablation) | MPR · DBLP/Epinions/Ciao | NDCG | Mixed |
| use MPR (M2) instead of BPR for average trustworthiness | PageRank · Ciao top-10 relevance | avg trustworthiness: 1.38 -> 1.05 | Hurt |
Closest papers by meaning
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- Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank (ICML 2024 · similarity 0.82)
- Fast Algorithms for Hypergraph PageRank with Applications to Semi-Supervised Learning (ICML 2024 · similarity 0.82)
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