Knowledge Graph Explanations
Knowledge Graph Explanations is a recommendable item justification framework that leverages structured knowledge graphs to explicitly trace and articulate the semantic relationships and contextual reasoning paths between user preferences and item recommendations.
82
Publications
5.8K
Citations
291
Authors
126
Institutions
Publications per year
2017–2026
78
Parents
82
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
2019 · 426 citations · Full text
Recurrent knowledge graph embedding for effective recommendation
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
Weizhi Ma, Min Zhang, Yue Cao et al. · 2019 · 219 citations · Full text
1–5 of 82
291
Rutgers, The State University of New Jersey, United States
3 publications · 183 citations
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3
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3
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1–5 of 291
126

Chinese Academy of Sciences
Beijing, China
7 h-index
18 publications
1.1K citations
Rutgers, The State University of New Jersey
New Brunswick, United States
5 h-index
19 publications
3.2K citations

Alibaba Group (China)
Hangzhou, China
5 h-index
13 publications
1.3K citations
University of Chinese Academy of Sciences
Beijing, China
5 h-index
11 publications
657 citations
Tsinghua University
Beijing, China
4 h-index
19 publications
2K citations

Vrije Universiteit Amsterdam
Amsterdam, The Netherlands
4 h-index
6 publications
678 citations
University of Siegen
Siegen, Germany
3 h-index
12 publications
368 citations
Max Planck Institute for Informatics
Saarbrücken, Germany
3 h-index
5 publications
174 citations
1–8 of 126
Repository · 10 publications · 278 citations
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6 publications · 231 citations
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4 publications · 232 citations
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Conference · 4 publications · 950 citations
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Conference · 3 publications · 187 citations
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