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Fast Maximal Clique Enumeration on Uncertain Graphs: A Pivot-based Approach

Summary: Pivot-based algorithms accelerate maximal (k, eta)-clique enumeration on uncertain graphs, replacing costly set-enumeration with a new pruning principle. Generalizable to any hereditary property; adds size-constraint pruning and graph-reduction techniques; validated on nine real graphs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6517
Venue
SIGMOD
Year
2022
Pagerank
6.1751704e-05
Overall Rank
5,556 | 61.89%
DOI
10.1145/3514221.3526143

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{dai_sigmod22,
        title = {{Fast Maximal Clique Enumeration on Uncertain Graphs: A Pivot-based Approach}},
        author = {Dai, Qiangqiang and Li, Rong-Hua and Liao, Meihao and Chen, Hongzhi and Wang, Guoren},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3526143},
        url = {https://dl.acm.org/doi/10.1145/3514221.3526143},
        year = {2022}
}

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