LargeEA: Aligning Entities for Large-scale Knowledge Graphs
Summary: LargeEA scales entity alignment to massive KGs with two channels: structure via METIS-CPS mini-batch partitioning enabling batch-local learning for any EA method, and name via NFF with seedless augmentation. It fuses structure and name features; DBP1M provides a large-scale EA benchmark. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Congcong Ge (Zhejiang University)
- 2. Xiaoze Liu (Zhejiang University)
- 3. Lu Chen (Zhejiang University)
- 4. Yunjun Gao (Zhejiang University)
- 5. Baihua Zheng (Singapore Management University)
BibTeX Citation
@article{ge_vldb22,
title = {{LargeEA: Aligning Entities for Large-scale Knowledge Graphs}},
author = {Ge, Congcong and Liu, Xiaoze and Chen, Lu and Gao, Yunjun and Zheng, Baihua},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {2},
pages = {237--245},
doi = {10.14778/3489496.3489504},
url = {https://doi.org/10.14778/3489496.3489504},
year = {2022}
}
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,398 | Real-time Workload Pattern Analysis for Large-scale Cloud Databases | 2023 | VLDB | 6.7248611e-05 |
| 6,806 | HongTu: Scalable Full-Graph GNN Training on Multiple GPUs | 2023 | SIGMOD | 5.7673207e-05 |
| 7,134 | PromptEM: Prompt-tuning for Low-resource Generalized Entity Matching | 2023 | VLDB | 5.6942765e-05 |
| 9,063 | Deep Active Alignment of Knowledge Graph Entities and Schemata | 2023 | SIGMOD | 5.3251649e-05 |
| 10,835 | NeutronTask: Scalable and Efficient Multi-GPU GNN Training with Task Parallelism | 2025 | VLDB | 5.093636e-05 |
| 11,226 | ZeroEA: A Zero-Training Entity Alignment Framework via Pre-Trained Language Model | 2024 | VLDB | 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 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 141 | Deep Entity Matching with Pre-Trained Language Models | 2021 | VLDB | 0.0002964847 |
| 176 | Deep Learning for Entity Matching: A Design Space Exploration | 2018 | SIGMOD | 0.00027191081 |
| 1,057 | YAGO3: A Knowledge Base from Multilingual Wikipedias | 2015 | CIDR | 0.00012387149 |
| 2,086 | PARIS: Probabilistic Alignment of Relations, Instances, and Schema | 2012 | VLDB | 9.1930537e-05 |
| 4,056 | A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs | 2020 | VLDB | 6.9344762e-05 |
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