Research map / Graph learning / Graph algorithms and clustering
Community Focusing: Yet Another Query-Dependent Community Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| replace best baseline with FLCF on Amazon | FLCF · Amazon | F1 (%): 89.9 -> 92.8 | Helped |
| FLCF instead of DCPC on DBLP | FLCF · DBLP | F1 (%): 86.2 -> 90.9 | Helped |
| FLCF instead of QDC on Youtube | FLCF · Youtube | F1 (%): 75.6 -> 69.9 | Hurt |
| FLCF instead of LCTC on LiveJournal | FLCF · LiveJournal | F1 (%): 79.0 -> 81.5 | Helped |
| FLCF instead of MDC on Orkut | FLCF · Orkut | F1 (%): 41.4 -> 53.2 | Helped |
| FLCF instead of MDC on Orkut (time) | FLCF · Orkut | time (s): 402.6 -> 0.018 | Helped |
| FLCF instead of DCPC on Youtube (time) | FLCF · Youtube | time (s): 1.39 -> 0.007 | Helped |
| FLCF instead of QDC on Amazon (conductance) | FLCF · Amazon | conductance: 0.416 -> 0.132 | Helped |
| FLCF instead of LCTC on Youtube (conductance) | FLCF · Youtube | conductance: 0.825 -> 0.831 | Hurt |
| FLCF instead of MDC on Youtube (geometric density) | FLCF · Youtube | geometric density: 0.94 -> 1.25 | Helped |
| add speed-up strategy (FLCF vs LCF) (ablation) | LCF · Amazon/DBLP | running time | Helped |
| local expansion (LCF/FLCF) instead of BASE (ablation) | BASE · Amazon/DBLP | minimum attention | No clear effect |
Closest papers by meaning
- Optimal Quasi-clique: Hardness, Equivalence with Densest-k-Subgraph, and Quasi-partitioned Community Mining (AAAI 2024 · similarity 0.86)
- Optimal community detection in dense bipartite graphs (NeurIPS 2025 · similarity 0.85)
- New Parallel and Streaming Algorithms for Directed Densest Subgraph (NeurIPS 2025 · similarity 0.84)
- Learning Persistent Community Structures in Dynamic Networks via Topological Data Analysis (AAAI 2024 · similarity 0.84)
- Faster Streaming and Scalable Algorithms for Finding Directed Dense Subgraphs in Large Graphs (ICML 2024 · similarity 0.83)
- SLRL: Semi-Supervised Local Community Detection Based on Reinforcement Learning (AAAI 2025 · similarity 0.83)
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