Location Recommendation Systems
Location Recommendation Systems is a computational framework within location intelligence that generates personalized suggestions of geographic locations by integrating spatial, temporal, and user behavioral data to predict and recommend places of potential interest to an individual user.
427
Publications
28.8K
Citations
1.2K
Authors
457
Institutions
Publications per year
2017–2026
176
Variants
Location Recommender Systems
Parents
427
Mining interesting locations and travel sequences from GPS trajectories
Yu Zheng, Lizhu Zhang, Xing Xie et al. · 2009 · 1.9K citations
Collaborative location and activity recommendations with GPS history data
Vincent W. Zheng, Yu Zheng, Xing Xie et al. · 2010 · 663 citations
Recommendations in location-based social networks: a survey
Jie Bao, Yu Zheng, David A. Wilkie et al. · GeoInformatica · 2015 · 564 citations
1–5 of 427
1.2K
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457
Microsoft Research Asia (China)
Beijing, China
20 h-index
47 publications
17.3K citations

University of Minnesota
Minneapolis, United States
12 h-index
36 publications
5.2K citations

The University of Queensland
Brisbane, Australia
11 h-index
28 publications
1.7K citations
Vellore Institute of Technology University
Vellore, India
11 h-index
17 publications
627 citations
Microsoft (United States)
Redmond, United States
11 h-index
15 publications
2.6K citations

Chinese Academy of Sciences
Beijing, China
9 h-index
17 publications
909 citations

City University of Hong Kong
Hong Kong, Hong Kong
9 h-index
17 publications
947 citations
Nanyang Technological University
Singapore, Singapore
8 h-index
19 publications
2.3K citations
1–8 of 457
11 publications · 596 citations
11
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IJGI · 9 publications · 235 citations
9
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TIST · 9 publications · 728 citations
9
h-index
TKDE · 8 publications · 800 citations
8
h-index
7 publications · 440 citations
7
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1–5