Gap-constrained Pattern Mining
Gap-Constrained Pattern Mining is a sequence mining methodology that restricts the distance between consecutive elements in a pattern to a predefined maximum gap threshold, thereby ensuring temporal or positional coherence in discovered sequential patterns.
41
Publications
1.6K
Citations
109
Authors
67
Institutions
Publications per year
2017–2026
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Parents
41
Mining Minimal Distinguishing Subsequence Patterns with Gap Constraints
Xiaonan Ji, James Bailey, Guozhu Dong · 2006 · 147 citations
Lukasz Golab, Howard Karloff, Flip Korn et al. · Proceedings of the VLDB Endowment · 2009 · 105 citations
Mining periodic patterns with gap requirement from sequences
Minghua Zhang, Ben Kao, David W. Cheung et al. · ACM Transactions on Knowledge Discovery from Data · 2007 · 100 citations
NOSEP: Nonoverlapping Sequence Pattern Mining With Gap Constraints
Youxi Wu, Yao Tong, Xingquan Zhu et al. · IEEE Transactions on Cybernetics · 2017 · 95 citations
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67

Hefei University of Technology
Hefei, China
12 h-index
16 publications
429 citations

Hebei University of Technology
Tianjin, China
11 h-index
36 publications
1.3K citations

University of Vermont
Burlington, United States
6 h-index
10 publications
252 citations
Florida Atlantic University
Boca Raton, United States
5 h-index
5 publications
251 citations

The University of Melbourne
Melbourne, Australia
3 h-index
7 publications
598 citations
Mininglamp (China)
Beijing, China
3 h-index
3 publications
64 citations

University of Pisa
Pisa, Italy
2 h-index
4 publications
117 citations
Wright State University
Dayton, United States
2 h-index
2 publications
242 citations
1–8 of 67
5 publications · 156 citations
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TKDD · 4 publications · 249 citations
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2 publications · 108 citations
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2 publications · 156 citations
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IJFCS · 1 publications · 27 citations
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