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DKE
2008
124views more  DKE 2008»
13 years 9 months ago
A MaxMin approach for hiding frequent itemsets
In this paper, we are proposing a new algorithmic approach for sanitizing raw data from sensitive knowledge in the context of mining of association rules. The new approach (a) rel...
George V. Moustakides, Vassilios S. Verykios
FIMI
2004
161views Data Mining» more  FIMI 2004»
13 years 10 months ago
ABS: Adaptive Borders Search of frequent itemsets
In this paper, we present an ongoing work to discover maximal frequent itemsets in a transactional database. We propose an algorithm called ABS for Adaptive Borders Search, which ...
Frédéric Flouvat, Fabien De Marchi, ...
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 9 months ago
Identifying bridging rules between conceptual clusters
1 A bridging rule in this paper has its antecedent and action from different conceptual clusters. We first design two algorithms for mining bridging rules between clusters in a dat...
Shichao Zhang, Feng Chen, Xindong Wu, Chengqi Zhan...
FIMI
2003
104views Data Mining» more  FIMI 2003»
13 years 10 months ago
AIM: Another Itemset Miner
We present a new algorithm for mining frequent itemsets. Past studies have proposed various algorithms and techniques for improving the efficiency of the mining task. We integrate...
Amos Fiat, Sagi Shporer
PODS
2009
ACM
134views Database» more  PODS 2009»
14 years 9 months ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...