Two new research papers explore advancements in data profiling techniques, focusing on the Desbordante tool. The first paper details optimizations for order dependency discovery algorithms, achieving up to a 10x performance improvement and reduced memory consumption. The second paper introduces support for Probabilistic Functional Dependency (pFD) discovery within Desbordante, analyzing its relationship with Approximate Functional Dependencies (AFDs) and comparing their performance. AI
IMPACT Enhances data profiling capabilities, potentially improving database query optimization, data cleaning, and anomaly detection.
RANK_REASON The cluster contains two academic papers published on arXiv detailing new algorithms and implementation techniques for data profiling tools.
- alphaXiv
- Approximate functional dependency
- arXiv
- CatalyzeX Code Finder for Papers
- Connected Papers
- CORE Recommender
- DagsHub
- Desbordante
- FASTOD
- Gotit.pub
- Hugging Face
- Influence Flower
- Litmaps
- ORDER
- Probabilistic Functional Dependency
- ScienceCast
- scite Smart Citations
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