ChARLES: Change-Aware Recovery of Latent Evolution Semantics in Relational Data
Summary: ChARLES yields semantic, human-readable summaries of changes between database snapshots, not exhaustive diff lists. It infers latent evolution by fitting regression lines over partitions and ranks transformations by accuracy-interpretability tradeoffs. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Shiyi He
- 2. Alexandra Meliou
- 3. Anna Fariha
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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 |
|---|---|---|---|---|
| 2,037 | OrpheusDB: Bolt-on Versioning for Relational Databases | 2017 | VLDB | 9.7120139e-05 |
| 5,280 | Explaining Dataset Changes for Semantic Data Versioning with Explain-Da-V | 2023 | VLDB | 5.5896735e-05 |
| 5,506 | Exploring Change – A New Dimension of Data Analytics | 2019 | VLDB | 5.473324e-05 |
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