ZooBP: Belief Propagation for Heterogeneous Networks
Summary: ZooBP derives a closed-form, provably convergent Belief Propagation solution for undirected heterogeneous graphs with multiple node/edge types. It runs in linear time—up to 600× faster than BP—and achieves 92.3% precision for fraud detection on a 3.3M-edge e-commerce graph. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Dhivya Eswaran (Carnegie Mellon University)
- 2. Stephan Günnemann (Technical University of Munich)
- 3. Christos Faloutsos (Carnegie Mellon University)
- 4. Disha Makhija (Flipkart)
- 5. Mohit Kumar (Flipkart)
BibTeX Citation
@article{eswaran_vldb17,
title = {{ZooBP: Belief Propagation for Heterogeneous Networks}},
author = {Eswaran, Dhivya and Günnemann, Stephan and Faloutsos, Christos and Makhija, Disha and Kumar, Mohit},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {5},
pages = {625--636},
doi = {10.14778/3055540.3055554},
url = {https://doi.org/10.14778/3055540.3055554},
year = {2017}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,666 | xFraud: Explainable Fraud Transaction Detection | 2022 | VLDB | 6.577136e-05 |
| 11,757 | Factorized Graph Representations for Semi-Supervised Learning from Sparse Data | 2020 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,970 | Linearized and Single-Pass Belief Propagation | 2015 | VLDB | 5.7303405e-05 |
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