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Blocking

Entity resolution (also known as entity matching, record linkage, or duplicate detection) is the task of finding records that refer to the same real-world entity across different data sources (e.g., data files, books, websites, and databases). (Source: Wikipedia)

Blocking is a crucial step in any entity resolution pipeline because a pair-wise comparison of all records across two data sources is infeasible. Blocking applies a computationally cheap method to generate a smaller set of candidate record pairs reducing the workload of the matcher. During matching a more expensive pair-wise matcher generates a final set of matching record pairs.

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Papers

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Showing 131–140 of 524 papers

TitleStatusHype
ConvCSNet: A Convolutional Compressive Sensing Framework Based on Deep Learning—0
Contextual Blocking Bandits—0
Autellix: An Efficient Serving Engine for LLM Agents as General Programs—0
A Logical Neural Network Structure With More Direct Mapping From Logical Relations—0
Contextual adversarial attack against aerial detection in the physical world—0
A Unified Deep Learning Architecture for Abuse Detection—0
Containerized Distributed Value-Based Multi-Agent Reinforcement Learning—0
Constrained Deployment Optimization in Integrated Access and Backhaul Networks—0
ALISE: Accelerating Large Language Model Serving with Speculative Scheduling—0
AdaFPP: Adapt-Focused Bi-Propagating Prototype Learning for Panoramic Activity Recognition—0
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