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Efficient k-Clique Count Estimation with Accuracy Guarantee

Summary: SR-kCCE pre-determines s, the number of uniformly sampled k-cliques required to meet a provable accuracy guarantee and to estimate sampling time. It stops refining the superset sample space when elapsed time ≈ estimated sampling time, balancing construction vs sampling and enabling efficient u.a.r. sampling. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
hdffa317410dc62ce
Venue
VLDB
Year
2024
Pagerank
5.4548071e-05
Overall Rank
7,775 | 47.73%
DOI
10.14778/3681954.3682032

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{chang_vldb24,
        title = {{Efficient k-Clique Count Estimation with Accuracy Guarantee}},
        author = {Chang, Lijun and Gamage, Rashmika and Yu, Jeffrey Xu},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {11},
        pages = {3707--3719},
        doi = {10.14778/3681954.3682032},
        url = {https://doi.org/10.14778/3681954.3682032},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
1,209 KClist++: A Simple Algorithm for Finding k-Clique Densest Subgraphs in Large Graphs 2020 VLDB 0.00011534572
3,412 Scaling Up k-Clique Densest Subgraph Detection 2023 SIGMOD 7.3251247e-05
3,610 Efficient k-Clique Listing: An Edge-Oriented Branching Strategy 2024 SIGMOD 7.1643588e-05
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