Aggregating maximal cliques in real-world graphs
Summary: Introduces ρ-dense aggregators: compact collections of dense clusters collectively covering all maximal cliques, avoiding redundant enumeration. Proves near-tight subexponential bounds and near-linear algorithms on bounded-degeneracy graphs, with substantial real-world speedups. (summarized by gpt-5.6-luna on Aug 17 2026)
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Authors
- 1. Noga Alon (Princeton University)
- 2. Sabyasachi Basu (Microsoft)
- 3. Shweta Jain (University of Utah)
- 4. Haim Kaplan (Google; Tel Aviv University)
- 5. Jakub Łącki (Google)
- 6. Blair D. Sullivan (University of Utah)
BibTeX Citation
@article{alon_vldb26,
title = {{Aggregating maximal cliques in real-world graphs}},
author = {Alon, Noga and Basu, Sabyasachi and Jain, Shweta and Kaplan, Haim and Łącki, Jakub and Sullivan, Blair D.},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {9},
pages = {2183--2195},
doi = {10.14778/3819518.3819543},
url = {https://doi.org/10.14778/3819518.3819543},
year = {2026}
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,981 | Accelerating Maximal Clique Enumeration via Graph Reduction | 2024 | VLDB | 6.329157e-05 |
| 13,768 | Scalable Community Detection via Parallel Correlation Clustering | 2021 | VLDB | - |
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