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ICDM
2005
IEEE
177views Data Mining» more  ICDM 2005»
15 years 3 months ago
Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian Databases
In data mining, enumerate the frequent or the closed patterns is often the first difficult task leading to the association rules discovery. The number of these patterns represen...
Loïck Lhote, François Rioult, Arnaud S...
GFKL
2005
Springer
105views Data Mining» more  GFKL 2005»
15 years 3 months ago
Implications of Probabilistic Data Modeling for Mining Association Rules
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. In the current literature, the properties of algorithms to mine ass...
Michael Hahsler, Kurt Hornik, Thomas Reutterer
ICDE
1998
IEEE
187views Database» more  ICDE 1998»
15 years 10 months ago
Mining Optimized Association Rules with Categorical and Numeric Attributes
?Mining association rules on large data sets has received considerable attention in recent years. Association rules are useful for determining correlations between attributes of a ...
Rajeev Rastogi, Kyuseok Shim
JCST
2008
119views more  JCST 2008»
14 years 9 months ago
Mining Frequent Generalized Itemsets and Generalized Association Rules Without Redundancy
This paper presents some new algorithms to efficiently mine max frequent generalized itemsets (g-itemsets) and essential generalized association rules (g-rules). These are compact ...
Daniel Kunkle, Donghui Zhang, Gene Cooperman
DASFAA
2004
IEEE
125views Database» more  DASFAA 2004»
15 years 1 months ago
Reducing Communication Cost in a Privacy Preserving Distributed Association Rule Mining
Data mining is a process that analyzes voluminous digital data in order to discover hidden but useful patterns from digital data. However, discovery of such hidden patterns has sta...
Mafruz Zaman Ashrafi, David Taniar, Kate A. Smith