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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

Showing 471480 of 524 papers

TitleStatusHype
Compression Artifacts Reduction by a Deep Convolutional NetworkCode0
Relation-aware Compositional Zero-shot Learning for Attribute-Object Pair RecognitionCode0
BFRFormer: Transformer-based generator for Real-World Blind Face RestorationCode0
Who's Afraid of Adversarial Queries? The Impact of Image Modifications on Content-based Image RetrievalCode0
Augmenting Rule-based DNS Censorship Detection at Scale with Machine LearningCode0
ML-CB: Machine Learning Canvas BlockCode0
chemmodlab: A Cheminformatics Modeling Laboratory for Fitting and Assessing Machine Learning ModelsCode0
AdGraph: A Graph-Based Approach to Ad and Tracker BlockingCode0
Weakly-Supervised Hierarchical Text ClassificationCode0
Understanding and Counteracting Feature-Level Bias in Click-Through Rate PredictionCode0
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