Synthesizing Type-Detection Logic for Rich Semantic Data Types using Open-source Code
Summary: Autotype synthesizes semantic-type detectors by mining code from positive examples and a keyword; it derives type-detection logic from execution traces. On a 112-type benchmark, it detects 84 with precision, boosting web-table discovery vs. baselines. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
BibTeX Citation
@inproceedings{yan_sigmod18,
title = {{Synthesizing Type-Detection Logic for Rich Semantic Data Types using Open-source Code}},
author = {Yan, Cong and He, Yeye},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3196888},
url = {https://dl.acm.org/doi/10.1145/3183713.3196888},
year = {2018}
}
Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,977 | Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks | 2024 | SIGMOD | 9.2760522e-05 |
| 2,093 | Sato: Contextual Semantic Type Detection in Tables | 2020 | VLDB | 9.0593586e-05 |
| 2,744 | Transform-Data-by-Example (TDE): An Extensible Search Engine for Data Transformations | 2018 | VLDB | 8.064168e-05 |
| 2,748 | Uni-Detect: A Unified Approach to Automated Error Detection in Tables | 2019 | SIGMOD | 8.0572603e-05 |
| 4,426 | Auto-Transform: Learning-to-Transform by Patterns | 2020 | VLDB | 6.601896e-05 |
| 5,102 | Towards Benchmarking Feature Type Inference for AutoML Platforms | 2021 | SIGMOD | 6.2705617e-05 |
| 7,742 | Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data Lakes | 2021 | SIGMOD | 5.4599258e-05 |
| 9,239 | Auto-Test: Learning Semantic-Domain Constraints for Unsupervised Error Detection in Tables | 2025 | SIGMOD | 5.2032182e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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