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ICDM
2005
IEEE
139views Data Mining» more  ICDM 2005»
15 years 4 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»
15 years 11 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
15 years 4 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»
15 years 11 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
15 years 4 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