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KDD
1999
ACM
220views Data Mining» more  KDD 1999»
15 years 1 months ago
Efficient Mining of Emerging Patterns: Discovering Trends and Differences
We introduce a new kind of patterns, called emerging patterns (EPs), for knowledge discovery from databases. EPs are defined as itemsets whose supports increase significantly from...
Guozhu Dong, Jinyan Li
KDD
2006
ACM
107views Data Mining» more  KDD 2006»
15 years 10 months ago
Out-of-core frequent pattern mining on a commodity PC
In this work we focus on the problem of frequent itemset mining on large, out-of-core data sets. After presenting a characterization of existing out-of-core frequent itemset minin...
Gregory Buehrer, Srinivasan Parthasarathy, Amol Gh...
ICDE
2004
IEEE
155views Database» more  ICDE 2004»
15 years 11 months ago
BIDE: Efficient Mining of Frequent Closed Sequences
Previous studies have presented convincing arguments that a frequent pattern mining algorithm should not mine all frequent patterns but only the closed ones because the latter lea...
Jianyong Wang, Jiawei Han
KDD
2007
ACM
179views Data Mining» more  KDD 2007»
15 years 3 months ago
Mining statistically important equivalence classes and delta-discriminative emerging patterns
The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
Jinyan Li, Guimei Liu, Limsoon Wong
PAKDD
2000
ACM
128views Data Mining» more  PAKDD 2000»
15 years 1 months ago
Efficient Detection of Local Interactions in the Cascade Model
Detection of interactions among data items constitutes an essential part of knowledge discovery. The cascade model is a rule induction methodology using levelwise expansion of a la...
Takashi Okada