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Spade: A Real-Time Fraud Detection Framework on Evolving Graphs

Summary: Spade: an incremental framework that maintains dense-subgraph (fraudulent community) detection on million-scale evolving transaction graphs in hundreds of microseconds. Offers batch/edge-group updates and APIs to plug suspiciousness semantics, incrementalizing peeling algorithms for up to 10^6× speedups vs static re-computation. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13491
Venue
VLDB
Year
2023
Pagerank
5.4360143e-05
Overall Rank
8,390 | 42.44%
DOI
10.14778/3570690.3570696

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{jiang_vldb23,
        title = {{Spade: A Real-Time Fraud Detection Framework on Evolving Graphs}},
        author = {Jiang, Jiaxin and Li, Yuan and He, Bingsheng and Hooi, Bryan and Chen, Jia and Kang, Johan Kok Zhi},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {3},
        pages = {461--469},
        doi = {10.14778/3570690.3570696},
        url = {https://doi.org/10.14778/3570690.3570696},
        year = {2023}
}

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