Pattern Discovery
Pattern Discovery is the systematic identification of recurring structures, trends, or relationships within time series data through exploratory analytical techniques to reveal inherent temporal dynamics not captured by formal models.
1.1K
Publications
75K
Citations
2.6K
Authors
993
Institutions
Publications per year
2017–2026
242
1.1K
Jaideep Srivastava, Robert Cooley, Mukund Deshpande et al. · ACM SIGKDD Explorations Newsletter · 2000 · 2.1K citations
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
1–5 of 1.1K
2.6K
35
h-index
16
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15
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14
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12
h-index
1–5 of 2.6K
993
University of California, Riverside
Riverside, United States
35 h-index
151 publications
27.2K citations
University of Illinois Urbana-Champaign
Urbana, United States
19 h-index
52 publications
4.4K citations
Carnegie Mellon University
Pittsburgh, United States
17 h-index
31 publications
2.4K citations
George Mason University
Fairfax, United States
16 h-index
38 publications
3.4K citations
IBM (United States)
Armonk, United States
16 h-index
45 publications
3.4K citations
IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
14 h-index
37 publications
3.1K citations
Tsinghua University
Beijing, China
13 h-index
35 publications
1.4K citations

University of Waterloo
Waterloo, Canada
13 h-index
40 publications
1.1K citations
1–8 of 993
TKDE · 39 publications · 4.1K citations
29
h-index
19 publications · 2.7K citations
18
h-index
16 publications · 543 citations
14
h-index
20 publications · 750 citations
14
h-index
Repository · 17 publications · 730 citations
14
h-index
1–5