Explainable Recommendation Models
Explainable Recommendation Models is a class of recommender systems that, as a genus, generate personalized suggestions for users, and, as a differentia, explicitly provide interpretable justifications for their recommendations to enhance transparency, trust, and user understanding.
135
Publications
9.6K
Citations
444
Authors
190
Institutions
Publications per year
2017–2026
115
Parents
135
Explaining collaborative filtering recommendations
Jonathan L. Herlocker, Joseph A. Konstan, John Riedl · 2000 · 1.7K citations
Explicit factor models for explainable recommendation based on phrase-level sentiment analysis
Yongfeng Zhang, Guokun Lai, Min Zhang et al. · 2014 · 799 citations
Explainable Recommendation a survey and new perspectives
2020 · 716 citations
1–5 of 135
444
Rutgers, The State University of New Jersey, United States
14 publications · 1.2K citations
12
h-index
5
h-index
5
h-index
4
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4
h-index
1–5 of 444
190
Tsinghua University
Beijing, China
9 h-index
17 publications
5.5K citations
Rutgers, The State University of New Jersey
New Brunswick, United States
8 h-index
18 publications
713 citations
Hong Kong Baptist University
Hong Kong, Hong Kong
5 h-index
9 publications
402 citations

Hefei University of Technology
Hefei, China
5 h-index
9 publications
347 citations

The University of Queensland
Brisbane, Australia
4 h-index
6 publications
150 citations
Rutgers Sexual and Reproductive Health and Rights
Utrecht, Netherlands
4 h-index
12 publications
449 citations

East China Normal University
Shanghai, China
3 h-index
7 publications
220 citations

Peking University
Beijing, China
3 h-index
4 publications
430 citations
1–8 of 190
Repository · 10 publications · 200 citations
10
h-index
10 publications · 686 citations
10
h-index
5 publications · 122 citations
5
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TKDE · 4 publications · 121 citations
4
h-index
4 publications · 179 citations
4
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1–5