Event Recommendation Systems
Event Recommendation Systems is a computational framework within event management systems that personalizes event suggestions to users by analyzing their preferences, behaviors, and contextual data, distinguishing it from general recommendation systems through its specialized focus on event-specific attributes such as time, location, attendance dynamics, and temporal constraints.
92
Publications
3.6K
Citations
271
Authors
124
Institutions
Publications per year
2017–2026
34
Parents
92
Hongzhi Yin, Yizhou Sun, Bin Cui et al. · 2013 · 335 citations
Recommending Social Events from Mobile Phone Location Data
Daniele Quercia, Neal Lathia, Francesco Calabrese et al. · 2010 · 233 citations · Full text
Hongzhi Yin, Bin Cui, Yizhou Sun et al. · ACM Transactions on Information Systems · 2014 · 137 citations
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IBM Research - Thomas J. Watson Research Center, United States
4 publications · 111 citations
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4
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1–5 of 271
124
University of Technology Sydney
Sydney, Australia
7 h-index
7 publications
623 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
20 publications
1.2K citations
Florida International University
Miami, United States
4 h-index
13 publications
392 citations

Huazhong University of Science and Technology
Wuhan, China
4 h-index
14 publications
358 citations
Institute of Information Engineering
Beijing, China
4 h-index
14 publications
730 citations
Tsinghua University
Beijing, China
4 h-index
11 publications
764 citations

St. John's University
New York, United States
4 h-index
4 publications
111 citations
University of Cambridge
Cambridge, United Kingdom
3 h-index
7 publications
561 citations
1–8 of 124
4 publications · 102 citations
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TKDE · 4 publications · 124 citations
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4 publications · 89 citations
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2 publications · 43 citations
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Repository · 2 publications · 48 citations
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