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Pytheas: Pattern-based Table Discovery in CSV Files

Summary: Pytheas uses pattern-based line classification and column-value coherency to discover tables in loosely structured CSVs. It achieves precision/recall above 95% (vs ~89/81), generalizes across countries, and provides a confidence measure for potential errors. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12101
Venue
VLDB
Year
2020
Pagerank
6.5777452e-05
Overall Rank
3,968 | 72.43%
DOI
10.14778/3407790.3407810

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
7,100 Mondrian: Spreadsheet Layout Detection 2022 SIGMOD 4.826163e-05
7,810 Pollock: A Data Loading Benchmark 2023 VLDB 4.6415099e-05
8,500 A Demonstration of KGLac: A Data Discovery and Enrichment Platform for Data Science 2021 VLDB 4.4920292e-05
11,423 Detecting Layout Templates in Complex Multiregion Files 2022 VLDB 4.1905499e-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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