Approximate Frequent Pattern Mining
Approximate Frequent Pattern Mining is a method in data mining that identifies frequent patterns under relaxed support constraints, allowing for the discovery of itemsets that approximately satisfy minimum frequency thresholds amidst noise or data incompleteness.
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3.5K
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163
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77
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2017–2026
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New algorithms for fast discovery of association rules
Mohammed J. Zaki, Srinivasan Parthasarathy, Mitsunori Ogihara et al. · 1997 · 1.1K citations
Approximating a collection of frequent sets
Foto Afrati, Aristides Gionis, Heikki Mannila · 2004 · 141 citations · Full text
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University of Wisconsin–Madison
Madison, United States
3 h-index
5 publications
205 citations
Ca' Foscari University of Venice
Venice, Italy
3 h-index
5 publications
135 citations

Sejong University
Seoul, South Korea
3 h-index
9 publications
306 citations
IBM (United States)
Armonk, United States
3 h-index
4 publications
217 citations
University of Illinois Urbana-Champaign
Urbana, United States
3 h-index
8 publications
455 citations

Harbin Institute of Technology
Harbin, China
2 h-index
8 publications
848 citations
Institute of Computing Technology
Beijing, China
2 h-index
2 publications
24 citations
University of Technology Sydney
Sydney, Australia
2 h-index
3 publications
51 citations
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TKDE · 6 publications · 378 citations
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