DataRinse: Semantic Transforms for Data preparation based on Code Mining
Summary: DataRinse statically mines large codebases to extract and recommend semantic, column‑level data‑preparation transforms for reuse across teams, not just isolated snippets. It clusters related expressions per field and offers human‑in‑the‑loop selection and application. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Ibrahim Abdelaziz
- 2. Julian Dolby
- 3. Udayan Khurana
- 4. Horst Samulowitz
- 5. Kavitha Srinivas
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 517 | Can Foundation Models Wrangle Your Data? | 2023 | VLDB | 0.00021169035 |
| 1,267 | Foofah: Transforming Data By Example | 2017 | SIGMOD | 0.00012936483 |
| 3,252 | Auto-Suggest: Learning-to-Recommend Data Preparation Steps Using Data Science Notebooks | 2020 | SIGMOD | 7.3178277e-05 |
| 3,478 | Transform-Data-by-Example (TDE): An Extensible Search Engine for Data Transformations | 2018 | VLDB | 7.054159e-05 |
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