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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 451–475 of 524 papers

TitleStatusHype
Saliency-Aware Spatio-Temporal Artifact Detection for Compressed Video Quality Assessment—0
A Stochastic Approximation Approach for Efficient Decentralized Optimization on Random NetworksCode0
Universal Prompt Optimizer for Safe Text-to-Image GenerationCode0
Spatial-Frequency Discriminability for Revealing Adversarial PerturbationsCode0
On Calibration of LLM-based Guard Models for Reliable Content ModerationCode0
From Neural Re-Ranking to Neural Ranking: Learning a Sparse Representation for Inverted IndexingCode0
Classification of social media Toxic comments using Machine learning modelsCode0
Wide-AdGraph: Detecting Ad Trackers with a Wide Dependency Chain GraphCode0
Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter WeatherCode0
Reinforcement Learning of Self Enhancing Camera Image and Signal ProcessingCode0
Towards Effective Planning Strategies for Dynamic Opinion NetworksCode0
Emergent Complexity via Multi-Agent CompetitionCode0
Foundation for unbiased cross-validation of spatio-temporal models for species distribution modelingCode0
Stochastic Substitute Training: A Gray-box Approach to Craft Adversarial Examples Against Gradient Obfuscation DefensesCode0
How Useful is Intermittent, Asynchronous Expert Feedback for Bayesian Optimization?Code0
The dynamic interplay between in-context and in-weight learning in humans and neural networksCode0
Towards Universal Dense Blocking for Entity ResolutionCode0
An efficient deep convolutional laplacian pyramid architecture for CS reconstruction at low sampling ratiosCode0
Deep Convolution Networks for Compression Artifacts ReductionCode0
Effective Tensor Completion via Element-wise Weighted Low-rank Tensor Train with Overlapping Ket AugmentationCode0
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
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