Implicit User Feedback
Implicit User Feedback is a type of user input in adaptive interfaces that constitutes indirect behavioral evidence, such as navigation patterns or interaction timing, distinguished from explicit feedback by its unobtrusive and involuntary nature in indicating user preferences or needs.
128
Publications
8.5K
Citations
421
Authors
154
Institutions
Publications per year
2017–2026
55
Parents
128
Personalized entity recommendation
Xiao Yu, Xiang Ren, Yizhou Sun et al. · 2014 · 745 citations
Evaluating implicit measures to improve web search
Steve Fox, Kuldeep Karnawat, Mark Mydland et al. · ACM Transactions on Information Systems · 2005 · 565 citations
W. Wulf, Ellis Cohen, William M. Corwin et al. · Communications of the ACM · 1974 · 491 citations · Full text
Modeling User Exposure in Recommendation
Dawen Liang, Laurent Charlin, James O. McInerney et al. · 2016 · 377 citations
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154

University of Glasgow
Glasgow, United Kingdom
9 h-index
17 publications
828 citations
Google (United States)
Mountain View, United States
8 h-index
39 publications
1.9K citations
Yahoo (United States)
Sunnyvale, United States
6 h-index
20 publications
516 citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
13 publications
4.2K citations
Microsoft (United States)
Redmond, United States
6 h-index
19 publications
3.3K citations
Microsoft Research Asia (China)
Beijing, China
5 h-index
9 publications
510 citations

University of Amsterdam
Amsterdam, The Netherlands
4 h-index
12 publications
232 citations
University of Science and Technology of China
Hefei, China
4 h-index
11 publications
571 citations
1–8 of 154
4 publications · 910 citations
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Repository · 4 publications · 77 citations
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TKDE · 3 publications · 99 citations
3
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2 publications · 104 citations
2
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2 publications · 172 citations
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