Knowledge Verification for Long-Tail Verticals
Summary: Knowledge verification for tail verticals; presents FACTY, a framework combining evidence from KBs, the web, and query logs with evidence fusion to verify triples. FACTY verifies 50% of correct tail knowledge at 84% precision; outperforms baselines. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Furong Li (National University of Singapore)
- 2. Xin Luna Dong (Amazon)
- 3. Anno Langen (Google)
- 4. Yang Li (Google)
BibTeX Citation
@article{li_vldb17,
title = {{Knowledge Verification for Long-Tail Verticals}},
author = {Li, Furong and Dong, Xin Luna and Langen, Anno and Li, Yang},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {11},
pages = {1370--1383},
doi = {10.14778/3137628.3137646},
url = {https://doi.org/10.14778/3137628.3137646},
year = {2017}
}
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,056 | A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs | 2020 | VLDB | 6.9344762e-05 |
| 6,320 | CERES: Distantly Supervised Relation Extraction from the Semi-Structured Web | 2018 | VLDB | 5.9150411e-05 |
| 7,628 | User Guidance for Efficient Fact Checking | 2019 | VLDB | 5.5798467e-05 |
| 8,921 | Generations of Knowledge Graphs: The Crazy Ideas and the Business Impact | 2023 | VLDB | 5.3483178e-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 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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