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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 326–350 of 524 papers

TitleStatusHype
Scalable Graph Convolutional Network Training on Distributed-Memory Systems—0
Scaling Author Name Disambiguation with CNF Blocking—0
School bus routing by maximizing trip compatibility—0
Secure State Estimation with Asynchronous Measurements against Malicious Measurement-data and Time-stamp Manipulation—0
Security Assessment and Impact Analysis of Cyberattacks in Integrated T&D Power Systems—0
Semi-Supervised Method using Gaussian Random Fields for Boilerplate Removal in Web Browsers—0
Sensitivity of DC Network Representation for GIC Analysis—0
Series Resonant Matrix Converter Topology for EV DC Fast Charging—0
Set-Transformer BeamsNet for AUV Velocity Forecasting in Complete DVL Outage Scenarios—0
ShallowBlocker: Improving Set Similarity Joins for Blocking—0
Shapley-Scarf Housing Markets: Respecting Improvement, Integer Programming, and Kidney Exchange—0
Should ChatGPT Write Your Breakup Text? Exploring the Role of AI in Relationship Dissolution—0
Simulating 2+1D Lattice Quantum Electrodynamics at Finite Density with Neural Flow Wavefunctions—0
Simultaneous Estimation of X-ray Back-Scatter and Forward-Scatter using Multi-Task Learning—0
Simultaneous Modeling of In Vivo and In Vitro Effects of Nondepolarizing Neuromuscular Blocking Drugs—0
Single Trajectory Conformal Prediction—0
Sitatapatra: Blocking the Transfer of Adversarial Samples—0
Smart Mobility Digital Twin Based Automated Vehicle Navigation System: A Proof of Concept—0
SMS Spam Detection and Classification to Combat Abuse in Telephone Networks Using Natural Language Processing—0
SOS: Systematic Offensive Stereotyping Bias in Word Embeddings—0
SparCML: High-Performance Sparse Communication for Machine Learning—0
Spatially Correlated Patterns in Adversarial Images—0
SQLR: Short-Term Memory Q-Learning for Elastic Provisioning—0
State space partitioning based on constrained spectral clustering for block particle filtering—0
Statistical Linear Regression Approach to Kalman Filtering and Smoothing under Cyber-Attacks—0
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