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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 226–250 of 524 papers

TitleStatusHype
Constrained Deployment Optimization in Integrated Access and Backhaul Networks—0
Collaborative Domain Blocking: Using federated NLP To Detect Malicious Domains—0
Dynamically meeting performance objectives for multiple services on a service mesh—0
Exploration Policies for On-the-Fly Controller Synthesis: A Reinforcement Learning ApproachCode0
Embedding Representation of Academic Heterogeneous Information Networks Based on Federated Learning—0
SOS: Systematic Offensive Stereotyping Bias in Word Embeddings—0
Calibrating Sequence likelihood Improves Conditional Language Generation—0
Multi-scale Attention Network for Single Image Super-ResolutionCode1
S^2-Transformer for Mask-Aware Hyperspectral Image ReconstructionCode1
EnergonAI: An Inference System for 10-100 Billion Parameter Transformer Models—0
Virtual Control Group: Measuring Hidden Performance Metrics—0
A hybrid transmission model for Plasmodium vivax accounting for superinfection, immunity and the hypnozoite reservoir—0
Non-Blocking Batch A* (Technical Report)—0
Rating the Crisis of Online Public Opinion Using a Multi-Level Index System—0
Network Coexistence Analysis of RIS-Assisted Wireless Communications—0
Impact of RoCE Congestion Control Policies on Distributed Training of DNNs—0
Content-aware Scalable Deep Compressed SensingCode1
Revisiting the Sample Adaptive Offset post-filter of VVC with Neural-Networks—0
Sudowoodo: Contrastive Self-supervised Learning for Multi-purpose Data Integration and PreparationCode1
With a little help from my friends: essentiality vs opportunity in group criticality—0
Resource Allocation in Multicore Elastic Optical Networks: A Deep Reinforcement Learning Approach—0
NeuralPassthrough: Learned Real-Time View Synthesis for VRCode1
Block-SCL: Blocking Matters for Supervised Contrastive Learning in Product Matching—0
The lattice of envy-free many-to-many matchings with contracts—0
Backdoor Attacks on Vision TransformersCode1
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