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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 91–100 of 524 papers

TitleStatusHype
Ethnicity sensitive author disambiguation using semi-supervised learningCode0
Detecting DGA domains with recurrent neural networks and side informationCode0
An efficient deep convolutional laplacian pyramid architecture for CS reconstruction at low sampling ratiosCode0
Learning to Discriminate Perturbations for Blocking Adversarial Attacks in Text ClassificationCode0
DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous RelaxationCode0
Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter WeatherCode0
Destruction of Image Steganography using Generative Adversarial NetworksCode0
DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic RegressionCode0
BFRFormer: Transformer-based generator for Real-World Blind Face RestorationCode0
Deep Convolution Networks for Compression Artifacts ReductionCode0
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