3 citations · 9 across the 10 of their papers we have counts for
5 papers · 1 filter
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…
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…
Blend: A Unified Data Discovery System
Mahdi Esmailoghli, Christoph Schnell, Renée J. Miller +1
Most research on data discovery has so far focused on improving individual discovery operators such as join, correlation, or union discovery. However, in practice, a combination of…
MATE: Multi-Attribute Table Extraction
Mahdi Esmailoghli, Jorge-Arnulfo Quiané-Ruiz, Ziawasch Abedjan
A core operation in data discovery is to find joinable tables for a given table. Real-world tables include both unary and n-ary join keys. However, existing table discovery systems…
Unsupervised String Transformation Learning for Entity Consolidation
Dong Deng, Wenbo Tao, Ziawasch Abedjan +7
Data integration has been a long-standing challenge in data management with many applications. A key step in data integration is entity consolidation. It takes a collection of clus…