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Approximately Counting Triangles in Large Graph Streams Including Edge Duplicates with a Fixed Memory Usage

Summary: One-pass streaming algorithm uniformly samples distinct edges from large graph streams with duplicates, achieving O(1) per-edge sampling and no extra memory. It infers triangle counts from samples, outperforming prior methods in accuracy and speed within the same memory footprint. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11835
Venue
VLDB
Year
2018
Pagerank
6.6603827e-05
Overall Rank
4,500 | 69.13%
DOI
10.14778/3149193.3149197

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Authors

BibTeX Citation

@article{wang_vldb18,
        title = {{Approximately Counting Triangles in Large Graph Streams Including Edge Duplicates with a Fixed Memory Usage}},
        author = {Wang, Pinghui and Qi, Yiyan and Sun, Yu and Zhang, Xiangliang and Tao, Jing and Guan, Xiaohong},
        journal = {PVLDB},
        series = {{VLDB} '18},
        doi = {10.14778/3149193.3149197},
        url = {https://doi.org/10.14778/3149193.3149197},
        year = {2018}
}

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