Knowledge Graph Alignment

Knowledge Graph Alignment is a computational method that identifies semantically equivalent entities and relationships across different knowledge graphs to enable interoperability and integration.

88

Publications

6.5K

Citations

349

Authors

131

Institutions

Publications per year

2017–2026

84

Authors

349

  1. WH
    Wei Hu

    Nanjing University, China

    9 publications · 1.5K citations

    9

    h-index

  2. ZS
    Zequn Sun

    Nanjing University, China

    9 publications · 1.5K citations

    9

    h-index

  3. YQ
    Yuzhong Qu

    Nanjing University, China

    6 publications · 1.2K citations

    6

    h-index

  4. JT
    Jiuyang Tang

    National University of Defense Technology, China

    6 publications · 377 citations

    6

    h-index

  5. MC
    Muhao Chen

    University of Southern California, United States

    6 publications · 1K citations

    6

    h-index

1–5 of 349

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 7 publications · 417 citations

    7

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 6 publications · 984 citations

    6

    h-index

  3. Neurocomputing

    4 publications · 101 citations

    4

    h-index

  4. Proceedings of the ACM Web Conference 2022

    Conference · 4 publications · 151 citations

    4

    h-index

  5. Expert Systems with Applications

    3 publications · 72 citations

    3

    h-index

1–5