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SIGMOD
1996
ACM
110views Database» more  SIGMOD 1996»
13 years 11 months ago
Mining Quantitative Association Rules in Large Relational Tables
We introduce the problem of mining association rules in large relational tables containing both quantitative and categorical attributes. An example of such an association might be...
Ramakrishnan Srikant, Rakesh Agrawal
KDD
2005
ACM
103views Data Mining» more  KDD 2005»
14 years 7 months ago
Fast discovery of unexpected patterns in data, relative to a Bayesian network
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Szymon Jaroszewicz, Tobias Scheffer
GFKL
2005
Springer
105views Data Mining» more  GFKL 2005»
14 years 28 days 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
PAKDD
2005
ACM
63views Data Mining» more  PAKDD 2005»
14 years 27 days ago
Pruning Derivative Partial Rules During Impact Rule Discovery
Because exploratory rule discovery works with data that is only a sample of the phenomena to be investigated, some resulting rules may appear interesting only by chance. Techniques...
Shiying Huang, Geoffrey I. Webb
SDM
2004
SIAM
271views Data Mining» more  SDM 2004»
13 years 8 months ago
A Foundational Approach to Mining Itemset Utilities from Databases
Most approaches to mining association rules implicitly consider the utilities of the itemsets to be equal. We assume that the utilities of itemsets may differ, and identify the hi...
Hong Yao, Howard J. Hamilton, Cory J. Butz