Scaling Up k-Clique Densest Subgraph Detection
Summary: Proposes SCT*-Index, a succinct clique-tree index that compactly stores k-cliques and enables direct retrieval for the k-clique densest subgraph problem. Introduces SCTL and SCTL* with graph reductions and batch processing, plus a sampling-based approximation for billion-scale graphs, delivering up to two orders of magnitude speedups over prior approaches. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yizhang He
- 2. Kai Wang
- 3. Wenjie Zhang
- 4. Xuemin Lin
- 5. Ying Zhang
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,320 | Accelerating Maximal Clique Enumeration via Graph Reduction | 2024 | VLDB | 4.7629325e-05 |
| 9,403 | A Counting-based Approach for Efficient k-Clique Densest Subgraph Discovery | 2024 | SIGMOD | 4.3441378e-05 |
| 9,406 | Efficient k-Clique Count Estimation with Accuracy Guarantee | 2024 | VLDB | 4.3441378e-05 |
| 10,072 | Efficient and Scalable Directed Densest Subgraph Discovery | 2026 | SIGMOD | 4.1945683e-05 |
| 10,517 | Faster and Efficient Density Decomposition via Proportional Response with Exponential Momentum | 2025 | SIGMOD | 4.1945683e-05 |
| 10,535 | In-depth Analysis of Densest Subgraph Discovery in a Unified Framework | 2025 | VLDB | 4.1945683e-05 |
| 10,681 | Efficient k-Clique Densest Subgraph Discovery: Towards Bridging Practice and Theory | 2025 | VLDB | 4.1945683e-05 |
| 11,048 | Efficient Algorithms for Density Decomposition on Large Static and Dynamic Graphs | 2024 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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