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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)

Paper ID
12608
Venue
VLDB
Year
2021
Pagerank
5.5393291e-05
Overall Rank
7,811 | 46.42%
DOI
10.14778/3476249.3476293

Incoming Non-self Citations Over Time

Authors

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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