BrewER: Entity Resolution On-Demand
Summary: BrewER performs entity resolution on demand, executing SQL over dirty data while progressively producing results equivalent to querying cleaned data. User priorities guide resolution, avoiding full-dataset cleaning and reducing resources for evolving or subset-focused workloads. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Luca Zecchini (University of Modena and Reggio Emilia)
- 2. Giovanni Simonini (University of Modena and Reggio Emilia)
- 3. Sonia Bergamaschi (University of Modena and Reggio Emilia)
- 4. Felix Naumann (Hasso Plattner Institute; University of Potsdam)
BibTeX Citation
@article{zecchini_vldb23,
title = {{BrewER: Entity Resolution On-Demand}},
author = {Zecchini, Luca and Simonini, Giovanni and Bergamaschi, Sonia and Naumann, Felix},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {12},
pages = {4026--4029},
doi = {10.14778/3611540.3611612},
url = {https://doi.org/10.14778/3611540.3611612},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,573 | Deduplicated Sampling On-Demand | 2025 | VLDB | 5.154741e-05 |
| 10,184 | Progressive Entity Matching: A Design Space Exploration | 2025 | SIGMOD | 5.0629036e-05 |
| 10,777 | IncreQueryFusion: On-demand Data Fusion Framework in Dynamic Data Lakes | 2026 | VLDB | 4.9769913e-05 |
| 10,887 | Can we trust LLM Self-Explanations for Entity Resolution? | 2026 | VLDB | 4.9769913e-05 |
| 11,404 | RadlER: Deduplicated Sampling On-Demand | 2025 | VLDB | 4.9769913e-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 |
|---|---|---|---|---|
| 134 | Deep Entity Matching with Pre-Trained Language Models | 2021 | VLDB | 0.00030042569 |
| 158 | Deep Learning for Entity Matching: A Design Space Exploration | 2018 | SIGMOD | 0.00028038831 |
| 428 | Big Data Integration | 2013 | VLDB | 0.00018457189 |
| 530 | Magellan: Toward Building Entity Matching Management Systems | 2016 | VLDB | 0.00016847532 |
| 5,199 | QuERy: A Framework for Integrating Entity Resolution with Query Processing | 2016 | VLDB | 6.2309669e-05 |
| 6,014 | Query-Driven Approach to Entity Resolution | 2013 | VLDB | 5.9112242e-05 |
| 7,263 | Entity Resolution On-Demand | 2022 | VLDB | 5.5693872e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 3,666 | Online Entity Resolution Using an Oracle | 2016 | VLDB |
| 2 | 11,404 | RadlER: Deduplicated Sampling On-Demand | 2025 | VLDB |
| 3 | 7,521 | SystemER: A Human-in-the-loop System for Explainable Entity Resolution | 2019 | VLDB |
| 4 | 10,538 | In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration | 2026 | SIGMOD |
| 5 | 3,787 | Entity Resolution with Evolving Rules | 2010 | VLDB |
| 6 | 2,645 | Progressive Approach to Relational Entity Resolution | 2014 | VLDB |
| 7 | 3,634 | NADEEF/ER: Generic and Interactive Entity Resolution | 2014 | SIGMOD |
| 8 | 5,052 | BEER: Blocking for Effective Entity Resolution | 2021 | SIGMOD |
| 9 | 5,199 | QuERy: A Framework for Integrating Entity Resolution with Query Processing | 2016 | VLDB |
| 10 | 7,263 | Entity Resolution On-Demand | 2022 | VLDB |