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20242026
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cs.DB2026

Understanding Domain-Aware Distribution Alignment in Budgeted Entity Matching

Nicholas Pulsone, Gregory Goren, Roee Shraga

Entity Matching (EM) is a core operation in the data integration pipeline, where records from different sources are compared to determine whether they refer to the same real-world…

cs.DB2026

BEACON: Budget-Aware Entity Matching Across Domains (Extended Technical Report)

Nicholas Pulsone, Roee Shraga, Gregory Goren

Entity Matching (EM)--the task of determining whether two data records refer to the same real-world entity--is a core task in data integration. Recent advances in deep learning hav…

cs.DB2025

Diverse Unionable Tuple Search: Novelty-Driven Discovery in Data Lakes [Technical Report]

Aamod Khatiwada, Roee Shraga, Renée J. Miller

Unionable table search techniques input a query table from a user and search for data lake tables that can contribute additional rows to the query table. The definition of unionabi…

cs.DB2025

Humans, Machine Learning, and Language Models in Union: A Cognitive Study on Table Unionability

Sreeram Marimuthu, Nina Klimenkova, Roee Shraga

Data discovery and table unionability in particular became key tasks in modern Data Science. However, the human perspective for these tasks is still under-explored. Thus, this rese…

cs.DB2025

Fuzzy Integration of Data Lake Tables

Aamod Khatiwada, Roee Shraga, Renée J. Miller

Data integration is an important step in any data science pipeline where the objective is to unify the information available in different datasets for comprehensive analysis. Full…