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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 181–190 of 524 papers

TitleStatusHype
Boosting Gradient for White-Box Adversarial Attacks—0
An introduction to Causal Modelling—0
Adversarial Distortion for Learned Video Compression—0
Em-K Indexing for Approximate Query Matching in Large-scale ER—0
Energy Efficiency Optimization in IRS-Enhanced mmWave Systems with Lens Antenna Array—0
Enhancing Model Defense Against Jailbreaks with Proactive Safety Reasoning—0
Embedding Representation of Academic Heterogeneous Information Networks Based on Federated Learning—0
EraseReLU: A Simple Way to Ease the Training of Deep Convolution Neural Networks—0
ERBlox: Combining Matching Dependencies with Machine Learning for Entity Resolution—0
ELIS: Efficient LLM Iterative Scheduling System with Response Length Predictor—0
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