Recommendation Engines
Recommendation Engines is a computational system that personalizes user experiences by predicting and suggesting relevant items or content based on individual preferences, behavioral patterns, and contextual data.
392
Publications
27.7K
Citations
1.2K
Authors
411
Institutions
Publications per year
2017–2026
165
392
F. Maxwell Harper, Joseph A. Konstan · ACM Transactions on Interactive Intelligent Systems · 2015 · 3.8K citations
Analysis of recommendation algorithms for e-commerce
Badrul Sarwar, George Karypis, Joseph A. Konstan et al. · 2000 · 1.8K citations · Full text
Abhinandan Das, Mayur Datar, Ashutosh Garg et al. · 2007 · 1.5K citations
The YouTube video recommendation system
James Davidson, Benjamin Liebald, Junning Liu et al. · 2010 · 1.2K citations
James R. Bennett, Stan Lanning · 2007 · 1.1K citations
1–5 of 392
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411

University of Minnesota
Minneapolis, United States
9 h-index
28 publications
17.3K citations
Google (United States)
Mountain View, United States
8 h-index
29 publications
18.2K citations

Polytechnic University of Bari
Bari, Italy
6 h-index
15 publications
331 citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
5 h-index
17 publications
2.1K citations
University of California, Berkeley
Berkeley, United States
5 h-index
12 publications
515 citations
Vellore Institute of Technology University
Vellore, India
5 h-index
7 publications
360 citations
IBM (United States)
Armonk, United States
4 h-index
17 publications
641 citations

DePaul University
Chicago, United States
4 h-index
9 publications
561 citations
1–8 of 411
11 publications · 657 citations
11
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Repository · 6 publications · 141 citations
7
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4 publications · 169 citations
5
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Repository · 4 publications · 175 citations
5
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PVLDB · 4 publications · 116 citations
4
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1–5