One Set to Cover All Maximal Cliques Approximately
Summary: Defines tau-cover: a vertex set hitting every maximal clique by at least tau. NP-hard and non-submodular; MCCb, MCC, EMCC; MCC uses incremental bounds, EMCC adaptive sampling; experiments show MCC faster with smaller covers, EMCC even smaller and faster. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Xiaofan Li (Swinburne University of Technology)
- 2. Rui Zhou (Swinburne University of Technology)
- 3. Lu Chen (Swinburne University of Technology)
- 4. Chengfei Liu (Swinburne University of Technology)
- 5. Qiang He (Swinburne University of Technology)
- 6. Yun Yang (Swinburne University of Technology)
BibTeX Citation
@inproceedings{li_sigmod22,
title = {{One Set to Cover All Maximal Cliques Approximately}},
author = {Li, Xiaofan and Zhou, Rui and Chen, Lu and Liu, Chengfei and He, Qiang and Yang, Yun},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3517881},
url = {https://dl.acm.org/doi/10.1145/3514221.3517881},
year = {2022}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,032 | Fast Maximal Quasi-clique Enumeration: A Pruning and Branching Co-Design Approach | 2023 | SIGMOD | 5.7222954e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 674 | Finding Maximal Cliques in Massive Networks by H*-graph | 2010 | SIGMOD | 0.00015081844 |
| 1,509 | Finding the Maximum Clique in Massive Graphs | 2017 | VLDB | 0.00010539891 |
| 5,095 | Pricing Influential Nodes in Online Social Networks | 2020 | VLDB | 6.3654556e-05 |
| 7,698 | Tight Trade-offs for the Maximum k-Coverage Problem in the General Streaming Model | 2019 | PODS | 5.5657914e-05 |
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