Temporal Pattern Discovery
Temporal Pattern Discovery is a computational methodology that identifies and characterizes recurring, evolving, or anomalous temporal structures within time-varying data by analyzing the sequential ordering, duration, and timing of events or states over time.
213
Publications
14.3K
Citations
508
Authors
247
Institutions
Publications per year
2017–2026
31
213
Rule discovery from time series
Gautam Das, King-Ip Lin, Heikki Mannila et al. · 1998 · 628 citations
Mining Frequent Spatio-Temporal Sequential Patterns
Huiping Cao, Nikos Mamoulis, David W. Cheung · 2006 · 284 citations
Mining partially periodic event patterns with unknown periods
Sheng Ma, Joseph L. Hellerstein · 2002 · 231 citations
1–5 of 213
508
Vignana Jyothi Institute of Management, India
25 publications · 1.2K citations
23
h-index
19
h-index
18
h-index
14
h-index
8
h-index
1–5 of 508
247
Osmania University
Hyderabad, India
15 h-index
16 publications
845 citations
Jordan University of Science and Technology
Irbid, Jordan
12 h-index
12 publications
710 citations
National Institute of Technology Warangal
Warangal, India
12 h-index
11 publications
553 citations
Vaagdevi College of Engineering
Bollikunta, India
11 h-index
10 publications
525 citations
IBM (United States)
Armonk, United States
7 h-index
13 publications
1.2K citations
National Central University
Taoyuan City, Taiwan
7 h-index
9 publications
769 citations
George Mason University
Fairfax, United States
7 h-index
17 publications
1.7K citations

Tamkang University
Taipei, Taiwan
6 h-index
8 publications
183 citations
1–8 of 247
TKDE · 13 publications · 898 citations
13
h-index
10 publications · 477 citations
10
h-index
4 publications · 78 citations
4
h-index
3 publications · 180 citations
3
h-index
3 publications · 177 citations
3
h-index
1–5