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Bursting Flow Query on Large Temporal Flow Networks

Summary: Proposes a bursting-flow query on temporal networks: maximize source-sink flow per time window (burstiness) to flag high-rate intervals. BFQ enumerates intervals and computes max-flows; BFQ* adds incremental updates reusing shared subflows for efficiency; validated on real transaction networks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7138
Venue
SIGMOD
Year
2025
Pagerank
5.093636e-05
Overall Rank
10,683 | 26.71%
DOI
10.1145/3709737

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Authors

BibTeX Citation

@inproceedings{xu_sigmod25,
        title = {{Bursting Flow Query on Large Temporal Flow Networks}},
        author = {Xu, Lyu and Jiang, Jiaxin and Choi, Byron and Xu, Jianliang and He, Bingsheng},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3709737},
        url = {https://dl.acm.org/doi/10.1145/3709737},
        year = {2025}
}

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