Spatio-Temporal Data Mining is a computational methodology within data mining that specifically discovers patterns, relationships, and anomalies from datasets characterized by both spatial and temporal dimensions through integrated analysis of geographic location and time-stamped occurrences.
579
Publications
31.7K
Citations
1.7K
Authors
635
Institutions
Publications per year
2017–2026
197
Parents
Publications
579
Yu Zheng · ACM Transactions on Intelligent Systems and Technology · 2015 · 1.6K citations
Computing, Data Science, Data Mining +15
Fosca Giannotti, Mirco Nanni, Fabio Pinelli et al. · 2007 · 1K citations
Computing, Data Science, Data Mining +14
1–5 of 579
Authors
1.7K
- SS
13
h-index
- YZ
12
h-index
- IL
11
h-index
- RA
10
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- BA
10
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1–5 of 1.7K
Institutions
635
University of Minnesota
Minneapolis, United States
19 h-index
75 publications
3.7K citations
University of Illinois Urbana-Champaign
Urbana, United States
15 h-index
36 publications
3.7K citations
Wuhan University
Wuhan, China
13 h-index
53 publications
2.9K citations
James Cook University
Townsville, Australia
10 h-index
27 publications
831 citations
Georgia State University
Atlanta, United States
10 h-index
33 publications
626 citations
Chinese Academy of Sciences
Beijing, China
10 h-index
34 publications
1.2K citations
Nanyang Technological University
Singapore, Singapore
9 h-index
14 publications
412 citations
University of Hong Kong
Pok Fu Lam, Hong Kong
9 h-index
24 publications
2.7K citations
1–8 of 635
Venues
- Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
13 publications · 2.3K citations
12
h-index
- IEEE Transactions on Knowledge and Data Engineering
TKDE · 11 publications · 1.5K citations
11
h-index
- International Journal of Geographical Information Systems
10 publications · 625 citations
10
h-index
- Expert Systems with Applications
9 publications · 347 citations
9
h-index
- Knowledge and Information Systems
8 publications · 276 citations
8
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1–5