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cs.DB2025
TransClean: Finding False Positives in Multi-Source Entity Matching under Real-World Conditions via Transitive Consistency
Fernando de Meer Pardo, Branka Hadji Misheva, Martin Braschler +1
We present TransClean, a method for detecting false positive predictions of entity matching algorithms under real-world conditions characterized by large-scale, noisy, and unlabele…
cs.DB2024★ 1 cited
GraLMatch: Matching Groups of Entities with Graphs and Language Models
Fernando De Meer Pardo, Claude Lehmann, Dennis Gehrig +5
In this paper, we present an end-to-end multi-source Entity Matching problem, which we call entity group matching, where the goal is to assign to the same group, records originatin…