Data Cleaning using Probabilistic Models of Integrity Constraints

By Simao Eduardo, Charles Sutton. 2016

3 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Marc-André Zöller
2. Marco F. Huber
3. Maryam Ashoori
4. Yufan Jiang
5. Li Yang
6. Xin He
7. Tien-Dung Nguyen

Citations in the corpus

• Benchmark and Survey of Automated Machine Learning Frameworks (2019, background): “Yet, most current approaches still aim to assist a human data scientist instead of fully automated data cleaning, (e.g., Krishnan et al., 2015; Khayyaty et al., 2015; Krishnan et al., 2016; Eduardo & Sutton, 2016; Rekatsinas et al., 2017).”
• Survey on Automated Machine Learning (2019, methodology): “in, 2001). Yet, most current approaches still aim to assist a human data scientist instead of fully automate data cleaning, e.g., (Krishnan et al., 2015; Khayyaty et al., 2015; Krishnan et al., 2016; Eduardo and Sutton, 2016; Rekatsinas et al., 2017). Krishnan and Wu (2019) proposed a semi-automatic”