Efficient Knowledge Graph Accuracy Evaluation
Summary: Efficient KG accuracy evaluation: statistical guarantees; cluster sampling reduces annotation costs. Weighted, two-stage, and stratified sampling enable incremental evaluation on evolving KGs (reservoir variant), yielding 60–80% cost reduction with preserved accuracy. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Junyang Gao (Duke University)
- 2. Xian Li (Amazon)
- 3. Yifan Ethan Xu (Amazon)
- 4. Bunyamin Sisman (Amazon)
- 5. Xin Luna Dong (Amazon)
- 6. Jun Yang (Duke University)
BibTeX Citation
@article{gao_vldb19,
title = {{Efficient Knowledge Graph Accuracy Evaluation}},
author = {Gao, Junyang and Li, Xian and Xu, Yifan Ethan and Sisman, Bunyamin and Dong, Xin Luna and Yang, Jun},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {11},
pages = {1679--1691},
doi = {10.14778/3342263.3342642},
url = {https://doi.org/10.14778/3342263.3342642},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,755 | Credible Intervals for Knowledge Graph Accuracy Estimation | 2025 | SIGMOD | 5.093636e-05 |
| 11,202 | Online Detection of Anomalies in Temporal Knowledge Graphs with Interpretability | 2024 | SIGMOD | 5.093636e-05 |
| 11,239 | Efficient and Reliable Estimation of Knowledge Graph Accuracy | 2024 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9 | Online Aggregation | 1997 | SIGMOD | 0.00077458002 |
| 1,323 | Data Cleaning: Overview and Emerging Challenges | 2016 | SIGMOD | 0.00011152602 |
| 1,736 | A Sample-and-Clean Framework for Fast and Accurate Query Processing on Dirty Data | 2014 | SIGMOD | 9.8984415e-05 |
| 5,899 | In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Sampling | 2017 | VLDB | 6.0469241e-05 |
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