Knowledge Graph Reasoning
Knowledge Graph Reasoning is a computational method that derives implicit, semantically consistent knowledge from explicit facts within a knowledge graph by leveraging logical, symbolic, or neural inference mechanisms to infer novel relationships, resolve inconsistencies, or complete missing information.
555
Publications
30.4K
Citations
2.1K
Authors
540
Institutions
Publications per year
2017–2026
531
Variants
Knowledge Graph Inference
555
Knowledge Graphs: Opportunities and Challenges
Ciyuan Peng, Feng Xia, Mehdi Naseriparsa et al. · Artificial Intelligence Review · 2023 · 604 citations · Full text
Computational Fact Checking from Knowledge Networks
Giovanni Luca Ciampaglia, Prashant Shiralkar, Luís M. Rocha et al. · PLoS ONE · 2015 · 498 citations · Full text
1–5 of 555
2.1K
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University of Maryland, Baltimore County, United States
6 publications · 242 citations
6
h-index
1–5 of 2.1K
540
Tsinghua University
Beijing, China
22 h-index
83 publications
4.5K citations

Chinese Academy of Sciences
Beijing, China
20 h-index
75 publications
3.1K citations
University of Chinese Academy of Sciences
Beijing, China
18 h-index
93 publications
5.9K citations

Zhejiang University
Hangzhou, China
14 h-index
65 publications
4K citations

Sun Yat-sen University
Guangzhou, China
14 h-index
43 publications
4.2K citations

National University of Defense Technology
Changsha, China
12 h-index
63 publications
5.2K citations
Wuhan University
Wuhan, China
12 h-index
27 publications
842 citations

Alibaba Group (China)
Hangzhou, China
11 h-index
27 publications
1.8K citations
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Repository · 66 publications · 2.5K citations
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Conference · 19 publications · 2.2K citations
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21 publications · 888 citations
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14 publications · 335 citations
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10 publications · 1.4K citations
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