The Smallest Extraction Problem
Summary: Introduces landmark grammars, a CFG family for templated HTML that reduces ambiguity in Web data extraction. Defines SEP to learn a grammar from related pages, with an unsupervised induction algorithm and an automatic extraction system showing improved performance. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Valerio Cetorelli (Roma Tre University)
- 2. Paolo Atzeni (Roma Tre University)
- 3. Valter Crescenzi (Roma Tre University)
- 4. Franco Milicchio (Roma Tre University)
BibTeX Citation
@article{cetorelli_vldb21,
title = {{The Smallest Extraction Problem}},
author = {Cetorelli, Valerio and Atzeni, Paolo and Crescenzi, Valter and Milicchio, Franco},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {11},
pages = {2445--2458},
doi = {10.14778/3476249.3476293},
url = {https://doi.org/10.14778/3476249.3476293},
year = {2021}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,395 | Web Record Extraction with Invariants | 2023 | VLDB | 5.2755515e-05 |
| 10,414 | Visual Template Inference for Data Extraction from Documents | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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