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
Variants
Knowledge Graph Embedding
824
1–5 of 824
2.5K
16
h-index
15
h-index
14
h-index
14
h-index
12
h-index
1–5 of 2.5K
616

Chinese Academy of Sciences
Beijing, China
29 h-index
154 publications
18.6K citations
Tsinghua University
Beijing, China
27 h-index
104 publications
24.1K citations
University of Chinese Academy of Sciences
Beijing, China
25 h-index
110 publications
5.5K citations
Tencent (China)
Shenzhen, China
21 h-index
51 publications
3K citations

Zhejiang University
Hangzhou, China
20 h-index
98 publications
5.9K citations
Institute of Information Engineering
Beijing, China
18 h-index
68 publications
12.7K citations
Wuhan University
Wuhan, China
16 h-index
39 publications
1.5K citations
Institute of Computing Technology
Beijing, China
16 h-index
65 publications
2.9K citations
1–8 of 616
Repository · 121 publications · 6.7K citations
38
h-index
Conference · 57 publications · 15.9K citations
37
h-index
TKDE · 25 publications · 3.9K citations
20
h-index
32 publications · 1.1K citations
20
h-index
23 publications · 713 citations
18
h-index
1–5