Retail Recommendation Algorithms
Retail Recommendation Algorithms is a computational method within the field of digital merchandising that systematically generates personalized product suggestions to consumers by analyzing behavioral, contextual, and transactional data to optimize retail outcomes such as sales, engagement, and customer satisfaction.
72
Publications
4.5K
Citations
222
Authors
107
Institutions
Publications per year
2017–2026
35
Parents
72
How Artificial Intelligence (AI) is Reshaping Retailing
Venkatesh Shankar · Journal of Retailing · 2018 · 387 citations
How artificial intelligence will affect the future of retailing
Abhijit Guha, Dhruv Grewal, Praveen K. Kopalle et al. · Journal of Retailing · 2021 · 300 citations
Challenging the long tail recommendation
Hongzhi Yin, Bin Cui, Jing Li et al. · Proceedings of the VLDB Endowment · 2012 · 275 citations
1–5 of 72
222
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2
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Advanced Telecommunications Research Institute International, Japan
2 publications · 125 citations
2
h-index
Advanced Telecommunications Research Institute International, Japan
2 publications · 125 citations
2
h-index
1–5 of 222
107

Chinese Academy of Sciences
Beijing, China
3 h-index
8 publications
322 citations
Fudan University
Shanghai, China
3 h-index
7 publications
276 citations

Peking University
Beijing, China
3 h-index
14 publications
1.8K citations
Northwestern University
Evanston, United States
2 h-index
4 publications
344 citations

Shanghai Jiao Tong University
Shanghai, China
2 h-index
10 publications
400 citations
University of Pennsylvania
Philadelphia, United States
2 h-index
3 publications
157 citations
University of Washington
Seattle, United States
2 h-index
3 publications
78 citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
2 h-index
2 publications
340 citations
1–8 of 107
3 publications · 280 citations
3
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3 publications · 713 citations
3
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3 publications · 97 citations
3
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3 publications · 370 citations
3
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2 publications · 200 citations
2
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1–5