DADER: Hands-Off Entity Resolution with Domain Adaptation
Summary: Hands-off deep ER via domain adaptation: DADER trains on labeled source ER data to enable zero- or few-label targets. Source-pair selection, six domain-adaptation strategies for alignment, and an open-source Python library with optional user labeling. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jianhong Tu
- 2. Xiaoyue Han
- 3. Ju Fan
- 4. Nan Tang
- 5. Chengliang Chai
- 6. Guoliang Li
- 7. Xiaoyong Du
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,828 | HAIPipe: Combining Human-generated and Machine-generated Pipelines for Data Preparation | 2023 | SIGMOD | 4.4364918e-05 |
| 9,439 | Rock: Cleaning Data by Embedding ML in Logic Rules | 2024 | SIGMOD | 4.3389137e-05 |
| 11,208 | When Automatic Filtering Comes to the Rescue: Pre-Computing Company Competitor Pairs in Owler | 2023 | SIGMOD | 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 |
| 740 | Distributed Representations of Tuples for Entity Resolution | 2018 | VLDB | 0.00017358024 |
| 1,821 | Synthesizing Entity Matching Rules by Examples | 2018 | VLDB | 0.00010406856 |
| 5,872 | Demonstration of Panda: A Weakly Supervised Entity Matching System | 2021 | VLDB | 5.2908178e-05 |
| 6,570 | Domain Adaptation for Deep Entity Resolution | 2022 | SIGMOD | 5.0017341e-05 |
| 6,873 | Cost-Effective Data Annotation using Game-Based Crowdsourcing | 2019 | VLDB | 4.8963037e-05 |
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