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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
13577
Venue
VLDB
Year
2024
Pagerank
4.3399748e-05
Overall Rank
9,412 | 34.59%
DOI
10.14778/3681954.3682032

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

Rank Cited Paper Year Venue Pagerank
1,570 KClist++: A Simple Algorithm for Finding k-Clique Densest Subgraphs in Large Graphs 2020 VLDB 0.00011311977
4,147 Scaling Up k-Clique Densest Subgraph Detection 2023 SIGMOD 6.4060893e-05
4,266 Efficient k-Clique Listing: An Edge-Oriented Branching Strategy 2024 SIGMOD 6.3006582e-05
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