Pattern Mining In Sequences
Pattern Mining in Sequences is a computational methodology within data mining that identifies recurring, significant, and semantically meaningful subsequences or structural regularities in ordered data sequences, distinguished by its focus on extracting temporal, positional, or sequential dependencies that characterize the inherent patterns in sequential datasets.
220
Publications
13K
Citations
533
Authors
284
Institutions
Publications per year
2017–2026
56
Parents
220
SPADE: An Efficient Algorithm for Mining Frequent Sequences
Mohammed J. Zaki · Machine Learning · 2001 · 1.8K citations · Full text
PrefixSpan,: mining sequential patterns efficiently by prefix-projected pattern growth
Jian Pei, Jiawei Han, Behzad Mortazavi-Asl et al. · 2005 · 1.8K citations
Rule discovery from time series
Gautam Das, King-Ip Lin, Heikki Mannila et al. · 1998 · 628 citations
1–5 of 220
533
16
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13
h-index
11
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Western Norway University of Applied Sciences, Norway
8 publications · 305 citations
8
h-index
1–5 of 533
284

Harbin Institute of Technology
Harbin, China
14 h-index
35 publications
1.5K citations

Jinan University
Guangzhou, China
9 h-index
13 publications
382 citations
Simon Fraser University
Burnaby, Canada
8 h-index
14 publications
7.8K citations
University of Illinois Chicago
Chicago, United States
8 h-index
9 publications
728 citations

Hebei University of Technology
Tianjin, China
7 h-index
22 publications
833 citations
Florida Atlantic University
Boca Raton, United States
7 h-index
7 publications
345 citations
National Dong Hwa University
Hualien City, Taiwan
6 h-index
6 publications
436 citations

University of Vermont
Burlington, United States
6 h-index
10 publications
322 citations
1–8 of 284
TKDE · 11 publications · 2.7K citations
11
h-index
TKDD · 10 publications · 365 citations
10
h-index
6 publications · 179 citations
6
h-index
6 publications · 102 citations
6
h-index
6 publications · 194 citations
6
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