DBScholar

Back to papers

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)

Paper ID
6599
Venue
SIGMOD
Year
2023
Pagerank
6.2230767e-05
Overall Rank
5,427 | 62.77%
DOI
10.1145/3588714

Incoming Non-self Citations Over Time

Authors

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.

Previous Page 1 / 1 Next

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.

Previous Page 1 / 1 Next

Semantically Similar Papers