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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)

Paper ID
6634
Venue
SIGMOD
Year
2023
Pagerank
7.2572837e-05
Overall Rank
3,613 | 75.22%
DOI
10.1145/3588923

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{he_sigmod23,
        title = {{Scaling Up k-Clique Densest Subgraph Detection}},
        author = {He, Yizhang and Wang, Kai and Zhang, Wenjie and Lin, Xuemin and Zhang, Ying},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3588923},
        url = {https://dl.acm.org/doi/10.1145/3588923},
        year = {2023}
}

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