CREST: Approximate k-Clique Counting in Real-World Networks via Refinement of Star-Based Sample Space
Summary: CREST accelerates Monte Carlo k-clique counting by refining star-based sample spaces, exactly eliminating countable subgraphs, and introducing an accuracy-aware stopping rule. It achieves up to 100× speedups while preserving target accuracy on real-world networks. (summarized by gpt-5.6-luna on Aug 17 2026)
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Authors
- 1. Yehyun Nam (Seoul National University)
- 2. Jihoon Jang (Seoul National University)
- 3. Kunsoo Park (Seoul National University)
- 4. Joong Chae Na (Sejong University)
- 5. Hyunjoon Kim (Hanyang University)
BibTeX Citation
@article{nam_vldb26,
title = {{CREST: Approximate k-Clique Counting in Real-World Networks via Refinement of Star-Based Sample Space}},
author = {Nam, Yehyun and Jang, Jihoon and Park, Kunsoo and Na, Joong Chae and Kim, Hyunjoon},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {9},
pages = {2331--2343},
doi = {10.14778/3819518.3819554},
url = {https://doi.org/10.14778/3819518.3819554},
year = {2026}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 131 | Discovering Large Dense Subgraphs in Massive Graphs | 2005 | VLDB | 0.00030242586 |
| 1,209 | KClist++: A Simple Algorithm for Finding k-Clique Densest Subgraphs in Large Graphs | 2020 | VLDB | 0.00011534572 |
| 3,189 | Efficient Maximum k-Plex Computation over Large Sparse Graphs | 2023 | VLDB | 7.5528776e-05 |
| 3,610 | Efficient k-Clique Listing: An Edge-Oriented Branching Strategy | 2024 | SIGMOD | 7.1643588e-05 |
| 7,775 | Efficient k-Clique Count Estimation with Accuracy Guarantee | 2024 | VLDB | 5.4548071e-05 |
| 7,807 | A Counting-based Approach for Efficient k-Clique Densest Subgraph Discovery | 2024 | SIGMOD | 5.4495451e-05 |
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