Auto-Transform: Learning-to-Transform by Patterns
Summary: Auto-Transform introduces transform-by-patterns (TBP): learning data transformations from patterns in large, cross-domain column pairs, without input/output examples. Multilingual, pattern-based harvesting yields transformations for data repairs and ETL automation, outperforming transform-by-example methods. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhongjun Jin (University of Michigan)
- 2. Yeye He (Microsoft)
- 3. Surajit Chaudhuri (Microsoft)
BibTeX Citation
@article{jin_vldb20,
title = {{Auto-Transform: Learning-to-Transform by Patterns}},
author = {Jin, Zhongjun and He, Yeye and Chaudhuri, Surajit},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {11},
pages = {2368--2381},
doi = {10.14778/3407790.3407831},
url = {https://doi.org/10.14778/3407790.3407831},
year = {2020}
}
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