I/O-Efficient Butterfly Counting at Scale
Summary: I/O-efficient butterfly counting on hierarchical memory; semi-witnessing counts butterflies via small subgraph witnesses, not full exploration. IOBufs nears I/O-optimal bounds, parallelizes well, and outperforms EMRC/BFC-EM while scaling to 37B edges and ~10^18 butterflies. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhibin Wang (Nanjing University)
- 2. Longbin Lai (Alibaba)
- 3. Yixue Liu (Nanjing University)
- 4. Bing Shui (Nanjing University)
- 5. Chen Tian (Nanjing University)
- 6. Sheng Zhong (Nanjing University)
BibTeX Citation
@inproceedings{wang_sigmod23,
title = {{I/O-Efficient Butterfly Counting at Scale}},
author = {Wang, Zhibin and Lai, Longbin and Liu, Yixue and Shui, Bing and Tian, Chen and Zhong, Sheng},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3588714},
url = {https://dl.acm.org/doi/10.1145/3588714},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,557 | Common Neighborhood Estimation over Bipartite Graphs under Local Differential Privacy | 2024 | SIGMOD | 5.2528121e-05 |
| 9,916 | Efficient Historical Butterfly Counting in Large Temporal Bipartite Networks via Graph Structure-aware Index | 2025 | VLDB | 5.1955087e-05 |
| 10,446 | Efficient and Effective Biclique Counting with Local Differential Privacy | 2026 | SIGMOD | 5.093636e-05 |
| 10,598 | Scalable Approximate Biclique Counting over Large Bipartite Graphs | 2026 | VLDB | 5.093636e-05 |
| 10,921 | Sectric: Towards Accurate, Privacy-preserving and Efficient Triangle Counting | 2025 | VLDB | 5.093636e-05 |
| 11,236 | Improving Graph Compression for Efficient Resource-Constrained Graph Analytics | 2024 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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