2 papers
cs.DB2026
Clean Me If You Can: A Large Collection of Real-World Addresses for Data Cleaning Benchmarking
Fatemeh Ahmadi, Tobias Bernhard, Mohamed Abdelmaksoud +3
There has been extensive research on automating and scaling data cleaning, i.e., the detection and correction of erroneous values in tabular data. Yet, existing approaches often pe…
cs.DB2026
RAMSeS: Robust and Adaptive Model Selection for Time-Series Anomaly Detection Algorithms
Mohamed Abdelmaksoud, Sheng Ding, Andrey Morozov +1
Time-series data vary widely across domains, making a universal anomaly detector impractical. Methods that perform well on one dataset often fail to transfer because what counts as…