NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding-Reference-Cited by-同舟云学术

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NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding

Published:2019-04 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE 35th International Conference on Data Engineering (ICDE)
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Author:

Zhang Yongqi,Yao Quanming,Shao Yingxia,Chen Lei

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8725877/8731337/08731371.pdf?arnumber=8731371

Cited by 87 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Heterogeneous Graph Contrastive Learning With Meta-Path Contexts and Adaptively Weighted Negative Samples;IEEE Transactions on Knowledge and Data Engineering;2024-10

2. M2ixKG: Mixing for harder negative samples in knowledge graph;Neural Networks;2024-09

3. Does Negative Sampling Matter? a Review With Insights Into its Theory and Applications;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-08

4. Negative-sample-free knowledge graph embedding;Data Mining and Knowledge Discovery;2024-07-09

5. Cascading Succession of Models for an Enhanced Long-Tail Discernment AI System;2024 IEEE World AI IoT Congress (AIIoT);2024-05-29

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