Problems , Methods , and Challenges in Comprehensive Data Cleansing

By H. Mueller, Johann Christoph Freytag. 2005

199 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. Sanjay Krishnan
2. M. Franklin
3. Eugene Wu
4. Ken Goldberg
5. Xuelong Li
6. Han Hu
7. Tat-seng Chua
8. Yonggang Wen

Citations in the corpus

• BoostClean: Automated Error Detection and Repair for Machine Learning (2017, background): “Numerous data quality surveys across the database, statistics, and scientific literature highlight the prevalence, variety, and importance of this class of errors, which include missing data, incorrect data, or inconsistent representations of the same logical data value [25,29,33,39].”
• A Survey on Data Quality: Classifying Poor Data (2015, background): “Duplicates [19], [53] occur when the same data appears repeated one or more times (e.”
• Toward Scalable Systems for Big Data Analytics: A Technology Tutorial (2014, background): “[99]–[101] provide a more in-depth treatment of this topic.”