Distributed Frequent Pattern Mining
Distributed Frequent Pattern Mining is a computational framework within frequent pattern mining that identifies recurring itemsets across multiple distributed datasets by leveraging parallel and distributed processing architectures to handle large-scale data.
146
Publications
9.5K
Citations
354
Authors
185
Institutions
Publications per year
2017–2026
36
Parents
146
Frequent pattern mining: current status and future directions
Jiawei Han, Hong Cheng, Dong Xin et al. · Data Mining and Knowledge Discovery · 2007 · 1.4K citations · Full text
Parallel and distributed association mining: a survey
Mohammed J. Zaki · IEEE Concurrency · 1999 · 478 citations
Haoyuan Li, Yi Wang, Dong Zhang et al. · 2008 · 441 citations
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Technion – Israel Institute of Technology
Haifa, Israel
7 h-index
16 publications
798 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
5 h-index
10 publications
1.1K citations

National Kaohsiung University of Applied Sciences
Kaohsiung City, Taiwan
4 h-index
6 publications
114 citations
Ca' Foscari University of Venice
Venice, Italy
4 h-index
6 publications
264 citations
Purdue University West Lafayette
West Lafayette, United States
4 h-index
7 publications
4.1K citations

Peking University
Beijing, China
3 h-index
6 publications
542 citations
Ho Chi Minh City University of Technology
Ho Chi Minh City, Vietnam
3 h-index
4 publications
92 citations
Institute of Computing Technology
Beijing, China
3 h-index
11 publications
635 citations
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5 publications · 224 citations
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4 publications · 151 citations
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4 publications · 1.4K citations
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4 publications · 93 citations
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3 publications · 149 citations
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