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Found 2 papers, 1 papers with code
Negative Sampling in Knowledge Graph Representation Learning: A Review
This comprehensive survey paper systematically reviews various negative sampling (NS) methods and their contributions to the success of KGRL.
TuckerDNCaching: high-quality negative sampling with tucker decomposition
Knowledge Graph Embedding (KGE) translates entities and relations of knowledge graphs (KGs) into a low-dimensional vector space, enabling an efficient way of predicting missing facts.
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