MiniClean: A Single-Machine System for Cleaning Big Graphs
Summary: MiniClean is a single-machine graph cleaning system unifying rule-based reasoning with ML for error detection and correction on billion-scale graphs. A CPU–GPU pipeline with memory bundling and compression, plus SIMD/pipelined/independent parallelism, delivers ~8x speedup vs a 32-node cluster. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Wenchao Bai
- 2. Wenfei Fan
- 3. Jiahui Jin
- 4. Daji Li
- 5. Jian Li
- 6. Shuhao Liu
- 7. Mingliang Ouyang
- 8. Qiang Yuan
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 221 | Deep Entity Matching with Pre-Trained Language Models | 2021 | VLDB | 0.00033121824 |
| 3,287 | GraphScope: A Unified Engine For Big Graph Processing | 2021 | VLDB | 7.2739447e-05 |
| 3,418 | CoroGraph: Bridging Cache Efficiency and Work Efficiency for Graph Algorithm Execution | 2024 | VLDB | 7.1188618e-05 |
| 8,146 | MiniGraph: Querying Big Graphs with a Single Machine | 2023 | VLDB | 4.5755031e-05 |
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