Large Scale Graph Mining with G-Miner
Summary: G-Miner: a distributed graph-mining system demo for interactive analytics. Highlights workload challenges and design choices affecting performance, expressiveness, and usability, with empirical comparison to existing systems. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Hongzhi Chen
- 2. Xiaoxi Wang
- 3. Chenghuan Huang
- 4. Juncheng Fang
- 5. Yifan Hou
- 6. Changji Li
- 7. James Cheng
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,064 | G-Tran: A High Performance Distributed Graph Database with a Decentralized Architecture | 2022 | VLDB | 5.7261007e-05 |
| 6,985 | CompressGraph: Efficient Parallel Graph Analytics with Rule-Based Compression | 2023 | SIGMOD | 4.8729387e-05 |
| 11,464 | Vertex-Centric Visual Programming for Graph Neural Networks | 2021 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4 | Pregel: A System for Large-Scale Graph Processing | 2010 | SIGMOD | 0.0019005923 |
| 6,709 | Big Graph Analytics Systems | 2016 | SIGMOD | 4.9529145e-05 |
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