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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 111120 of 524 papers

TitleStatusHype
Detecting DGA domains with recurrent neural networks and side informationCode0
DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic RegressionCode0
Evaluating Blocking Biases in Entity MatchingCode0
d-blink: Distributed End-to-End Bayesian Entity ResolutionCode0
DABT: A Dependency-aware Bug Triaging MethodCode0
Compression Artifacts Reduction by a Deep Convolutional NetworkCode0
Deep Convolution Networks for Compression Artifacts ReductionCode0
A Systematic Approach to Blocking Convolutional Neural NetworksCode0
Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter WeatherCode0
Pushing the Limits of Extreme Weather: Constructing Extreme Heatwave Storylines with Differentiable Climate ModelsCode0
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