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» An Approximate Approach for Mining Recently Frequent Itemset...
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KDD
2007
ACM
179views Data Mining» more  KDD 2007»
14 years 2 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
DATAMINE
1999
152views more  DATAMINE 1999»
13 years 8 months ago
Discovery of Frequent DATALOG Patterns
Discovery of frequent patterns has been studied in a variety of data mining settings. In its simplest form, known from association rule mining, the task is to discover all frequent...
Luc Dehaspe, Hannu Toivonen
CINQ
2004
Springer
116views Database» more  CINQ 2004»
14 years 16 days ago
A Survey on Condensed Representations for Frequent Sets
Abstract. Solving inductive queries which have to return complete collections of patterns satisfying a given predicate has been studied extensively the last few years. The specific...
Toon Calders, Christophe Rigotti, Jean-Franç...
DMKD
2003
ACM
96views Data Mining» more  DMKD 2003»
14 years 2 months ago
Using transposition for pattern discovery from microarray data
We analyze expression matrices to identify a priori interesting sets of genes, e.g., genes that are frequently co-regulated. Such matrices provide expression values for given biol...
François Rioult, Jean-François Bouli...
DASFAA
2010
IEEE
225views Database» more  DASFAA 2010»
13 years 9 months ago
Mining Regular Patterns in Data Streams
Discovering interesting patterns from high-speed data streams is a challenging problem in data mining. Recently, the support metric-based frequent pattern mining from data stream h...
Syed Khairuzzaman Tanbeer, Chowdhury Farhan Ahmed,...