Knowledge Graph Embeddings

Knowledge Graph Embedding is a representation learning method that maps entities and relations in a knowledge graph to low-dimensional vector spaces while preserving their structural and semantic properties.

824

Publications

76.1K

Citations

2.5K

Authors

616

Institutions

Publications per year

2017–2026

776

Authors

2.5K

  1. WH
    Wei Hu

    Nanjing University, China

    18 publications · 1.9K citations

    16

    h-index

  2. ZS
    Zequn Sun

    Nanjing University, China

    16 publications · 1.9K citations

    15

    h-index

  3. HC
    Huajun Chen

    Zhejiang University, China

    17 publications · 1.3K citations

    14

    h-index

  4. JL
    Jens Lehmann

    University of Bonn, Germany

    17 publications · 671 citations

    14

    h-index

  5. MC
    Muhao Chen

    University of Southern California, United States

    15 publications · 2.1K citations

    12

    h-index

1–5 of 2.5K

Venues

  1. arXiv (Cornell University)

    Repository · 121 publications · 6.7K citations

    38

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 57 publications · 15.9K citations

    37

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 25 publications · 3.9K citations

    20

    h-index

  4. Knowledge-Based Systems

    32 publications · 1.1K citations

    20

    h-index

  5. IEEE Access

    23 publications · 713 citations

    18

    h-index

1–5