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» Mining Frequent Itemsets Using Support Constraints
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ICDM
2005
IEEE
139views Data Mining» more  ICDM 2005»
14 years 1 months ago
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
Yongge Wang, Xintao Wu
DATAMINE
2010
166views more  DATAMINE 2010»
13 years 7 months ago
Optimal constraint-based decision tree induction from itemset lattices
In this article we show that there is a strong connection between decision tree learning and local pattern mining. This connection allows us to solve the computationally hard probl...
Siegfried Nijssen, Élisa Fromont
ISCC
2002
IEEE
147views Communications» more  ISCC 2002»
14 years 12 days ago
A new method for finding generalized frequent itemsets in generalized association rule mining
Generalized association rule mining is an extension of traditional association rule mining to discover more informative rules, given a taxonomy. In this paper, we describe a forma...
Kritsada Sriphaew, Thanaruk Theeramunkong
IDA
2002
Springer
13 years 7 months ago
Optimization of association rule mining queries
Levelwise algorithms (e.g., the Apriori algorithm) have been proved eective for association rule mining from sparse data. However, in many practical applications, the computation ...
Baptiste Jeudy, Jean-François Boulicaut
PKDD
2005
Springer
129views Data Mining» more  PKDD 2005»
14 years 29 days ago
Interestingness is Not a Dichotomy: Introducing Softness in Constrained Pattern Mining
Abstract. The paradigm of pattern discovery based on constraints was introduced with the aim of providing to the user a tool to drive the discovery process towards potentially inte...
Stefano Bistarelli, Francesco Bonchi