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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 126–150 of 524 papers

TitleStatusHype
Cooperative Beamforming and RISs Association for Multi-RISs Aided Multi-Users MmWave MIMO Systems through Graph Neural Networks—0
Advancing Direct Convolution using Convolution Slicing Optimization and ISA Extensions—0
Blocking Collapsed Gibbs Sampler for Latent Dirichlet Allocation Models—0
Blocking Bandits—0
A Neural Network Model of Continual Learning with Cognitive Control—0
A4 : Evading Learning-based Adblockers—0
Blocking and Other Enhancements for Bottom-Up Model Generation Methods—0
BlockDoor: Blocking Backdoor Based Watermarks in Deep Neural Networks—0
An Ensemble Blocking Scheme for Entity Resolution of Large and Sparse Datasets—0
Block-Based Multi-Scale Image Rescaling—0
Block based Adaptive Compressive Sensing with Sampling Rate Control—0
An Efficient Style Virtual Try on Network for Clothing Business Industry—0
Accelerating Parallel Stochastic Gradient Descent via Non-blocking Mini-batches—0
A Real-Time Adaptive Multi-Stream GPU System for Online Approximate Nearest Neighborhood Search—0
Don't Stop Me Now: Embedding Based Scheduling for LLMs—0
Block and Detail: Scaffolding Sketch-to-Image Generation—0
BLCS: Brain-Like based Distributed Control Security in Cyber Physical Systems—0
An Effective Dereverberation Algorithm by Fusing MVDR and MCLP—0
Bi-Phasic Quasistatic Brain Communication for Fully Untethered Connected Brain Implants—0
BioSpaun: A large-scale behaving brain model with complex neurons—0
Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)—0
Detecting Unknown DGAs without Context Information—0
Analysis of Intelligent Reflecting Surface-Enhanced Mobility Through a Line-of-Sight State Transition Model—0
A Deep Dive into the Connections Between the Renormalization Group and Deep Learning in the Ising Model—0
Better Not to Propagate: Understanding Edge Uncertainty and Over-smoothing in Signed Graph Neural Networks—0
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