GPU-Accelerated Graph Label Propagation for Real-Time Fraud Detection
Summary: GLP is a GPU-based graph label propagation framework that enables real-time fraud detection on TaoBao's large user-interaction graphs. It offers expressive APIs and GPU-centric optimizations that exploit community structure and power-law properties, delivering 8.2x single-GPU speedup over in-house multicore pipelines on billion-scale workloads. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chang Ye (Singapore Management University)
- 2. Yuchen Li (Singapore Management University)
- 3. Bingsheng He (National University of Singapore)
- 4. Zhao Li (Alibaba)
- 5. Jianling Sun (Zhejiang University)
BibTeX Citation
@inproceedings{ye_sigmod21,
title = {{GPU-Accelerated Graph Label Propagation for Real-Time Fraud Detection}},
author = {Ye, Chang and Li, Yuchen and He, Bingsheng and Li, Zhao and Sun, Jianling},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3452774},
url = {https://dl.acm.org/doi/10.1145/3448016.3452774},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 11 of 11 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,081 | Incremental Maintenance for Non-Distributive Aggregate Functions | 2002 | VLDB | 9.0742282e-05 |
| 2,468 | GPU-Accelerated Subgraph Enumeration on Partitioned Graphs | 2020 | SIGMOD | 8.4178183e-05 |
| 2,601 | Community Detection in Social Networks: An In-depth Benchmarking Study with a Procedure-Oriented Framework | 2015 | VLDB | 8.2335436e-05 |
| 2,789 | iBFS: Concurrent Breadth-First Search on GPUs | 2016 | SIGMOD | 8.0116036e-05 |
| 3,653 | Realtime Top-k Personalized PageRank over Large Graphs on GPUs | 2020 | VLDB | 7.1288161e-05 |
| 4,207 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD | 6.7343908e-05 |
| 5,300 | Parallel Personalized PageRank on Dynamic Graphs | 2018 | VLDB | 6.1896851e-05 |
| 7,716 | Accelerating Exact Constrained Shortest Paths on GPUs | 2021 | VLDB | 5.4683652e-05 |
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