Efficient and Reliable Estimation of Knowledge Graph Accuracy

Summary: Replaces Wald-based confidence intervals for KG accuracy estimation with Wilson-based intervals adapted to complex sampling designs, eliminating zero-width and overshooting issues. Delivers up to 2× reliability improvement while preserving or improving sampling efficiency across KG sizes/topologies. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13467
Venue: VLDB
Year: 2024
Pagerank: 4.1905499e-05
Overall Rank: 11,032 | 23.33%
DOI: 10.14778/3665844.3665865

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Stefano Marchesin
2. Gianmaria Silvello

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,486	Credible Intervals for Knowledge Graph Accuracy Estimation	2025	SIGMOD	4.1905499e-05

Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,629	Data Cleaning: Overview and Emerging Challenges	2016	SIGMOD	0.00011073148
2,177	A Sample-and-Clean Framework for Fast and Accurate Query Processing on Dirty Data	2014	SIGMOD	9.371335e-05
2,321	High-Throughput Vector Similarity Search in Knowledge Graphs	2023	SIGMOD	9.0359336e-05
2,853	Building, Maintaining, and Using Knowledge Bases: A Report from the Trenches	2013	SIGMOD	8.0147968e-05
3,716	Saga: A Platform for Continuous Construction and Serving of Knowledge At Scale	2022	SIGMOD	6.8170433e-05
5,546	Growing and Serving Large Open-domain Knowledge Graphs	2023	SIGMOD	5.4457186e-05
5,900	In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Sampling	2017	VLDB	5.2797112e-05
6,555	Knowledge Verification for Long-Tail Verticals	2017	VLDB	5.0076317e-05
6,690	Efficient Knowledge Graph Accuracy Evaluation	2019	VLDB	4.9575975e-05
6,959	Efficiently Answering Durability Prediction Queries	2021	SIGMOD	4.8805791e-05

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