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ICDM
2005
IEEE
139views Data Mining» more  ICDM 2005»
13 years 11 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
KDD
2006
ACM
198views Data Mining» more  KDD 2006»
14 years 6 months ago
CFI-Stream: mining closed frequent itemsets in data streams
Mining frequent closed itemsets provides complete and condensed information for non-redundant association rules generation. Extensive studies have been done on mining frequent clo...
Nan Jiang, Le Gruenwald
CIKM
2005
Springer
13 years 11 months ago
Frequent pattern discovery with memory constraint
We explore in this paper a practicably interesting mining task to retrieve frequent itemsets with memory constraint. As opposed to most previous works that concentrate on improvin...
Kun-Ta Chuang, Ming-Syan Chen
KDD
2004
ACM
148views Data Mining» more  KDD 2004»
14 years 5 months ago
Interestingness of frequent itemsets using Bayesian networks as background knowledge
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Szymon Jaroszewicz, Dan A. Simovici
SAC
2010
ACM
13 years 10 months ago
Mining interesting sets and rules in relational databases
In this paper we propose a new and elegant approach toward the generalization of frequent itemset mining to the multirelational case. We define relational itemsets that contain i...
Bart Goethals, Wim Le Page, Michael Mampaey