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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 481490 of 524 papers

TitleStatusHype
d-blink: Distributed End-to-End Bayesian Entity ResolutionCode0
SINBAD: Saliency-informed detection of breakage caused by ad blockingCode0
BlueTempNet: A Temporal Multi-network Dataset of Social Interactions in Bluesky SocialCode0
Percival: Making In-Browser Perceptual Ad Blocking Practical With Deep LearningCode0
Physics-Informed Heterogeneous Graph Neural Networks for DC Blocker PlacementCode0
Multi-Channel Deep Networks for Block-Based Image Compressive SensingCode0
Efficient MPI-based Communication for GPU-Accelerated Dask ApplicationsCode0
Collaborative Tracking Learning for Frame-Rate-Insensitive Multi-Object TrackingCode0
Robust one-shot estimation over shared networks in the presence of denial-of-service attacksCode0
Effective Model of Loop Extrusion Predicts Chromosomal DomainsCode0
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