Incremental Frequent Pattern Mining
Incremental Frequent Pattern Mining is a computational method in the field of data mining that dynamically updates the set of frequent patterns in response to changes in the transaction database, thereby avoiding the need to recompute patterns from scratch.
205
Publications
14.2K
Citations
462
Authors
201
Institutions
Publications per year
2017–2026
51
Parents
205
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
Sequential PAttern mining using a bitmap representation
Jay Ayres, Jason Flannick, Johannes Gehrke et al. · 2002 · 1.1K citations
Discovery of Multiple-Level Association Rules from Large Databases
Jiawei Han, Yongjian Fu · 1995 · 923 citations
1–5 of 205
462
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Western Norway University of Applied Sciences, Norway
17 publications · 771 citations
14
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9
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7
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1–5 of 462
201

Sejong University
Seoul, South Korea
16 h-index
52 publications
2.4K citations

National University of Kaohsiung
Kaohsiung City, Taiwan
14 h-index
23 publications
1.1K citations

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
11 h-index
28 publications
985 citations

National Sun Yat-sen University
Kaohsiung City, Taiwan
9 h-index
10 publications
382 citations
Western Norway University of Applied Sciences
Bergen, Norway
8 h-index
9 publications
244 citations

Harbin Institute of Technology
Harbin, China
8 h-index
19 publications
839 citations
University of Illinois Urbana-Champaign
Urbana, United States
7 h-index
20 publications
7K citations

National Taiwan University
Taipei, Taiwan
7 h-index
20 publications
1.4K citations
1–8 of 201
13 publications · 787 citations
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8 publications · 205 citations
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8 publications · 292 citations
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8 publications · 255 citations
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TKDE · 6 publications · 942 citations
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