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
Parents
88
Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks
Zhichun Wang, Qingsong Lv, Xiaohan Lan et al. · 2018 · 633 citations · Full text
Bootstrapping Entity Alignment with Knowledge Graph Embedding
Zequn Sun, Wei Hu, Qinghe Zhang et al. · 2018 · 531 citations · Full text
Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network
Kun Xu, Liwei Wang, Mo Yu et al. · 2019 · 261 citations · Full text
1–5 of 88
349
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131

National University of Defense Technology
Changsha, China
9 h-index
28 publications
1.5K citations
Nanjing University
Nanjing, China
9 h-index
34 publications
6.2K citations
Tsinghua University
Beijing, China
8 h-index
21 publications
1.6K citations
Tencent (China)
Shenzhen, China
7 h-index
26 publications
1.8K citations

Zhejiang University
Hangzhou, China
5 h-index
15 publications
596 citations

Chinese Academy of Sciences
Beijing, China
4 h-index
8 publications
454 citations

UNSW Sydney
Sydney, Australia
4 h-index
4 publications
333 citations
University of California, Los Angeles
Los Angeles, United States
4 h-index
6 publications
691 citations
1–8 of 131
TKDE · 7 publications · 417 citations
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Conference · 6 publications · 984 citations
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4 publications · 101 citations
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Conference · 4 publications · 151 citations
4
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3 publications · 72 citations
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