Time Series Pattern Recognition
Time Series Pattern Recognition is a systematic methodology within the broader field of pattern recognition that specializes in identifying temporal structures, recurring sequences, and dynamic dependencies in ordered data through time-aware models and feature extraction techniques.
1.1K
Publications
83.7K
Citations
2.9K
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1K
Institutions
Publications per year
2017–2026
446
Parents
1.1K
Backpropagation through time: what it does and how to do it
Paul J. Werbos · Proceedings of the IEEE · 1990 · 4.9K citations
Fast subsequence matching in time-series databases
Christos Faloutsos, M. Ranganathan, Yannis Manolopoulos · 1994 · 1.7K citations · Full text
Experiencing SAX: a novel symbolic representation of time series
Jessica Lin, Eamonn Keogh, Wei Li et al. · Data Mining and Knowledge Discovery · 2007 · 1.6K citations
Computing, Data Science, Mathematics +12
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University of California, Riverside
Riverside, United States
33 h-index
117 publications
24.1K citations

Monash University
Melbourne, Australia
17 h-index
46 publications
17.2K citations
George Mason University
Fairfax, United States
13 h-index
27 publications
3.4K citations
Carnegie Mellon University
Pittsburgh, United States
13 h-index
25 publications
2.8K citations

South China University of Technology
Guangzhou, China
12 h-index
44 publications
1.9K citations
Shandong University
Jinan, China
12 h-index
39 publications
1.4K citations
Tsinghua University
Beijing, China
12 h-index
21 publications
1K citations
University of California, Los Angeles
Los Angeles, United States
11 h-index
27 publications
2.5K citations
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30 publications · 9.5K citations
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32 publications · 1.5K citations
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28 publications · 2K citations
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19 publications · 1.2K citations
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18 publications · 971 citations
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