Synthesizing Extraction Rules from User Examples with SEER
Summary: SEER enables end-to-end IE by letting users highlight text and synthesize rules from a few examples. It offers rule suggestions users can accept or reject, jump-starting rule development as a data-efficient alternative to large labeled data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Maeda F. Hanafi
- 2. Azza Abouzied
- 3. Laura Chiticariu
- 4. Yunyao Li
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,237 | New Trends on Exploratory Methods for Data Analytics | 2017 | VLDB | 5.1435341e-05 |
| 8,344 | Exploring the Data Wilderness through Examples | 2019 | SIGMOD | 4.5428111e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 287 | Declarative Information Extraction Using Datalog with Embedded Extraction Predicates | 2007 | VLDB | 0.00028971272 |
| 6,534 | Automatic Rule Refinement for Information Extraction | 2010 | VLDB | 5.0244622e-05 |
| 13,388 | VINERy: A Visual IDE for Information Extraction | 2015 | VLDB | - |
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