Frequent Subsequence Mining
Frequent Subsequence Mining is a data mining technique that identifies subsequences occurring with a frequency exceeding a predefined threshold within a sequence database, distinguishing it from other pattern mining methods by its focus on ordered but non-contiguous occurrences in sequential data.
156
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11.1K
Citations
372
Authors
194
Institutions
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2017–2026
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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
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Simon Fraser University
Burnaby, Canada
8 h-index
27 publications
9.5K citations

University of Hong Kong
Pok Fu Lam, Hong Kong
6 h-index
17 publications
651 citations
IBM (United States)
Armonk, United States
5 h-index
6 publications
505 citations

Harbin Institute of Technology
Harbin, China
5 h-index
7 publications
404 citations
Ho Chi Minh City University of Science
Ho Chi Minh City, Vietnam
5 h-index
6 publications
149 citations
Wright State University
Dayton, United States
4 h-index
6 publications
324 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
6 publications
303 citations

Data61
Sydney, Australia
4 h-index
8 publications
604 citations
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7 publications · 284 citations
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4 publications · 64 citations
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4 publications · 75 citations
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