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BrewER: Entity Resolution On-Demand

Summary: BrewER enables on‑demand, prioritized entity resolution by progressively evaluating SQL selection/projection queries over dirty data and returning results as if issued on cleaned data according to a user-defined priority. Avoids full dataset cleaning for fast, resource-efficient, query-aware ER suited to interactive or frequently-changing data. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13257
Venue
VLDB
Year
2023
Pagerank
4.3324933e-05
Overall Rank
9,463 | 34.24%
DOI
10.14778/3611540.3611612

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
9,854 Progressive Entity Matching: A Design Space Exploration 2025 SIGMOD 4.2652623e-05
10,625 Deduplicated Sampling On-Demand 2025 VLDB 4.1905499e-05
10,812 RadlER: Deduplicated Sampling On-Demand 2025 VLDB 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

Rank Cited Paper Year Venue Pagerank
219 Deep Entity Matching with Pre-Trained Language Models 2021 VLDB 0.00033354456
293 Deep Learning for Entity Matching: A Design Space Exploration 2018 SIGMOD 0.00028661817
394 Big Data Integration 2013 VLDB 0.0002447017
705 Magellan: Toward Building Entity Matching Management Systems 2016 VLDB 0.00017779048
5,594 QuERy: A Framework for Integrating Entity Resolution with Query Processing 2016 VLDB 5.416945e-05
6,179 Query-Driven Approach to Entity Resolution 2013 VLDB 5.1645342e-05
7,930 Entity Resolution On-Demand 2022 VLDB 4.6089604e-05
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