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A framework for annotating CSV-like data

Summary: Framework to annotate CSV-like data and noisy variants with metadata via an extended regex selection language and annotation rules. The approach yields an output-sensitive, input-linear evaluator; real-data experiments confirm practical efficiency. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11563
Venue
VLDB
Year
2016
Pagerank
5.7257102e-05
Overall Rank
7,015 | 51.88%
DOI
10.14778/2983200.2983208

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{arenas_vldb16,
        title = {{A framework for annotating CSV-like data}},
        author = {Arenas, Marcelo and Maturana, Francisco and Riveros, Cristian and Vrgoč, Domagoj},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {11},
        pages = {876--887},
        doi = {10.14778/2983200.2983208},
        url = {https://doi.org/10.14778/2983200.2983208},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
2,348 Document Spanners for Extracting Incomplete Information: Expressiveness and Complexity 2018 PODS 8.7135317e-05
2,619 Constant Delay Algorithms for Regular Document Spanners 2018 PODS 8.336529e-05
4,168 Pytheas: Pattern-based Table Discovery in CSV Files 2020 VLDB 6.8570481e-05
7,803 Pollock: A Data Loading Benchmark 2023 VLDB 5.5418222e-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.

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