Knowledge Graph Benchmarking
Knowledge Graph Benchmarking is a systematic evaluation framework that distinguishes itself by assessing the performance, quality, and interoperability of knowledge graphs through standardized datasets, tasks, and metrics within the domain of knowledge representation and reasoning.
90
Publications
7.8K
Citations
384
Authors
163
Institutions
Publications per year
2017–2026
86
Parents
90
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Zhiqing Sun, Zhihong Deng, Jian‐Yun Nie et al. · arXiv (Cornell University) · 2019 · 771 citations · Full text
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex\n Space
Zhiqing Sun, Zhihong Deng, Jian‐Yun Nie et al. · arXiv (Cornell University) · 2019 · 751 citations · Full text
Learning from Noisy Labels with Distillation
Yuncheng Li, Yale Song, Liangliang Cao et al. · 2017 · 543 citations
KG-BERT: BERT for Knowledge Graph Completion
Liang Yao, Chengsheng Mao, Yuan Luo · arXiv (Cornell University) · 2019 · 381 citations · Full text
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163
Tsinghua University
Beijing, China
7 h-index
15 publications
487 citations

Zhejiang University
Hangzhou, China
7 h-index
45 publications
3.4K citations
University of Bonn
Bonn, Germany
6 h-index
16 publications
289 citations

Alibaba Group (China)
Hangzhou, China
4 h-index
15 publications
441 citations

University of Cagliari
Cagliari, Italy
3 h-index
6 publications
122 citations
Zhejiang University of Science and Technology
Hangzhou, China
3 h-index
9 publications
531 citations
University of Mannheim
Mannheim, Germany
3 h-index
6 publications
1.3K citations

Sun Yat-sen University
Guangzhou, China
3 h-index
11 publications
1K citations
1–8 of 163
Repository · 13 publications · 2.1K citations
12
h-index
6 publications · 1.8K citations
6
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Conference · 3 publications · 154 citations
3
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TPAMI · 2 publications · 45 citations
2
h-index
2 publications · 56 citations
2
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1–5