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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 176–200 of 524 papers

TitleStatusHype
Restoration of the JPEG Maximum Lossy Compressed Face Images with Hourglass Block based on Early Stopping Discriminator—0
GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node ClassificationCode1
Path-Specific Counterfactual Fairness for Recommender SystemsCode1
Improved Projection-free Online Continuous Submodular Maximization—0
Image Classification of Stroke Blood Clot Origin using Deep Convolutional Neural Networks and Visual Transformers—0
Machine Unlearning: its nature, scope, and importance for a "delete culture"—0
Road Planning for Slums via Deep Reinforcement LearningCode1
Spatial-Frequency Discriminability for Revealing Adversarial PerturbationsCode0
Simultaneous Modeling of In Vivo and In Vitro Effects of Nondepolarizing Neuromuscular Blocking Drugs—0
Fast Distributed Inference Serving for Large Language Models—0
A CSI Dataset for Wireless Human Sensing on 80 MHz Wi-Fi Channels—0
Time-Selective RNN for Device-Free Multi-Room Human Presence Detection Using WiFi CSI—0
Pre-trained Embeddings for Entity Resolution: An Experimental Analysis [Experiment, Analysis & Benchmark]Code1
Sparkly: A Simple yet Surprisingly Strong TF/IDF Blocker for Entity MatchingCode1
Partition-based Stability of Coalitional Games—0
Observability Blocking for Functional Privacy of Linear Dynamic Networks—0
Classification of social media Toxic comments using Machine learning modelsCode0
Protecting User Privacy in Online Settings via Supervised Learning—0
Secure State Estimation with Asynchronous Measurements against Malicious Measurement-data and Time-stamp Manipulation—0
Fault diagnosis for PV arrays considering dust impact based on transformed graphical feature of characteristic curves and convolutional neural network with CBAM modules—0
Tracker Meets Night: A Transformer Enhancer for UAV TrackingCode1
Dynamic EM Ray Tracing for Large Urban Scenes with Multiple Receivers—0
Model Extraction Attacks on Split Federated Learning—0
X-Former: In-Memory Acceleration of Transformers—0
Advancing Direct Convolution using Convolution Slicing Optimization and ISA Extensions—0
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