Knowledge Graph Evaluation
Knowledge Graph Evaluation is a systematic academic methodology for assessing the quality, completeness, and effectiveness of knowledge graphs through defined metrics and benchmarks that differentiate it from general data evaluation techniques by focusing specifically on symbolic knowledge representation, relational structure, and semantic accuracy.
71
Publications
4.9K
Citations
272
Authors
129
Institutions
Publications per year
2017–2026
60
Parents
71
Deriving Validity Time in Knowledge Graph
Julien Leblay, Melisachew Wudage Chekol · 2018 · 403 citations · Full text
Linked data quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO
Michael Färber, Frederic Bartscherer, Carsten Menne et al. · Semantic Web · 2017 · 344 citations · Full text
KnowEdu: A System to Construct Knowledge Graph for Education
Penghe Chen, Yu Lu, Vincent W. Zheng et al. · IEEE Access · 2018 · 261 citations · Full text
A retrospective of knowledge graphs
Jihong Yan, Chengyu Wang, Wenliang Cheng et al. · Frontiers of Computer Science · 2016 · 158 citations
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129
University of Mannheim
Mannheim, Germany
5 h-index
11 publications
2.1K citations
Tsinghua University
Beijing, China
3 h-index
7 publications
482 citations
University of Science and Technology of China
Hefei, China
3 h-index
20 publications
924 citations

Zhejiang University
Hangzhou, China
3 h-index
8 publications
179 citations
University of Bonn
Bonn, Germany
3 h-index
7 publications
118 citations
Leipzig University
Leipzig, Germany
3 h-index
4 publications
180 citations

Universität Innsbruck
Innsbruck, Austria
2 h-index
9 publications
236 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
2 h-index
6 publications
536 citations
1–8 of 129
4 publications · 389 citations
4
h-index
3 publications · 94 citations
3
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3 publications · 1.6K citations
3
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2 publications · 68 citations
2
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2 publications · 160 citations
2
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1–5