mlsanityData to 7 Oct 2026

Subsampling for Knowledge Graph Embedding Explained

arXiv 2209.12801 ↗First posted 13 Sep 2022cs.AI cs.CL cs.LGcited by 2

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Abstract (arXiv)

In this article, we explain the recent advance of subsampling methods in knowledge graph embedding (KGE) starting from the original one used in word2vec.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 9 of its 12 references that are in the map. First posted on arXiv 13 Sep 2022.

Builds on

9 of 12 references.

References · 9

  1. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,462
  2. 2014Embedding Entities and Relations for Learning and Inference in Knowledge Basescited by 929
  3. 2016Complex Embeddings for Simple Link Predictioncited by 897
  4. 2019RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Spacecited by 893
  5. 2017Convolutional 2D Knowledge Graph Embeddingscited by 729
  6. 2019Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Predictioncited by 133
  7. 2020Structure Aware Negative Sampling in Knowledge Graphscited by 26
  8. 2022Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation Learningcited by 12
  9. 2021Unified Interpretation of Softmax Cross-Entropy and Negative Sampling: With Case Study for Knowledge Graph Embeddingcited by 7

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Cited by year

Citing papers per year: 2023: 2.

2 papers.

  1. 2023Does Pre-trained Language Model Actually Infer Unseen Links in Knowledge Graph Completion?cited by 1
  2. 2023Model-based Subsampling for Knowledge Graph Completioncited by 0