Distributed Graph Embedding with Information-Oriented Random Walks
Summary: DistGER scales to billion-edge graphs by using information-centric random walks and a multi-proximity streaming partitioner to maximize locality and balance. An access-locality-optimized distributed Skip-Gram yields 2.3–129× speedups, ~45% less cross-machine traffic and >10% downstream gains vs prior frameworks. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Peng Fang (Huazhong University of Science and Technology)
- 2. Arijit Khan (Aalborg University)
- 3. Siqiang Luo (Nanyang Technological University)
- 4. Fang Wang (Huazhong University of Science and Technology)
- 5. Dan Feng (Huazhong University of Science and Technology)
- 6. Zhenli Li (Huazhong University of Science and Technology)
- 7. Wei Yin (Huazhong University of Science and Technology)
- 8. Yuchao Cao (Huazhong University of Science and Technology)
BibTeX Citation
@article{fang_vldb23,
title = {{Distributed Graph Embedding with Information-Oriented Random Walks}},
author = {Fang, Peng and Khan, Arijit and Luo, Siqiang and Wang, Fang and Feng, Dan and Li, Zhenli and Yin, Wei and Cao, Yuchao},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {7},
pages = {1643--1656},
doi = {10.14778/3587136.3587140},
url = {https://doi.org/10.14778/3587136.3587140},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,695 | GENTI: GPU-powered Walk-based Subgraph Extraction for Scalable Representation Learning on Dynamic Graphs | 2024 | VLDB | 5.7990641e-05 |
| 8,821 | Efficient Unsupervised Community Search with Pre-trained Graph Transformer | 2024 | VLDB | 5.3624668e-05 |
| 10,616 | Terark-DS: A High-Performance and Storage-Efficient Key-Value Separation Storage Engine on Disaggregated Storage | 2026 | VLDB | 5.093636e-05 |
| 11,172 | Efficient Approximation of Kemeny’s Constant for Large Graphs | 2024 | SIGMOD | 5.093636e-05 |
| 11,243 | TIGER: Training Inductive Graph Neural Network for Large-scale Knowledge Graph Reasoning | 2024 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 223 | AliGraph: A Comprehensive Graph Neural Network Platform | 2019 | VLDB | 0.00024182473 |
| 1,863 | ByteGNN: Efficient Graph Neural Network Training at Large Scale | 2022 | VLDB | 9.5950349e-05 |
| 1,968 | Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank | 2020 | VLDB | 9.3752727e-05 |
| 2,221 | Streaming Graph Partitioning: An Experimental Study | 2018 | VLDB | 8.9260308e-05 |
| 2,953 | Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching | 2022 | VLDB | 7.9237794e-05 |
| 3,362 | Experimental Analysis of Streaming Algorithms for Graph Partitioning | 2019 | SIGMOD | 7.4833791e-05 |
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| 1 | 4,912 | HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training | 2022 | SIGMOD |
| 2 | 11,228 | FlowWalker: A Memory-efficient and High-performance GPU-based Dynamic Graph Random Walk Framework | 2024 | VLDB |
| 3 | 1,246 | Distributed Evaluation of Subgraph Queries Using Worst-case Optimal Low-Memory Dataflows | 2018 | VLDB |
| 4 | 1,875 | Large-Scale Distributed Graph Computing Systems: An Experimental Evaluation | 2015 | VLDB |
| 5 | 2,640 | Scalable and Efficient Full-Graph GNN Training for Large Graphs | 2023 | SIGMOD |
| 6 | 1,968 | Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank | 2020 | VLDB |
| 7 | 5,305 | Parallel Training of Knowledge Graph Embedding Models: A Comparison of Techniques | 2022 | VLDB |
| 8 | 7,201 | An I/O-Efficient Disk-based Graph System for Scalable Second-Order Random Walk of Large Graphs | 2022 | VLDB |
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