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DAWAK
2006
Springer
13 years 11 months ago
Two New Techniques for Hiding Sensitive Itemsets and Their Empirical Evaluation
Many privacy preserving data mining algorithms attempt to selectively hide what database owners consider as sensitive. Specifically, in the association-rules domain, many of these ...
Ahmed HajYasien, Vladimir Estivill-Castro
PKDD
2005
Springer
129views Data Mining» more  PKDD 2005»
14 years 1 months 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
PPOPP
2005
ACM
14 years 1 months ago
A sampling-based framework for parallel data mining
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
Shengnan Cong, Jiawei Han, Jay Hoeflinger, David A...
KDD
2005
ACM
92views Data Mining» more  KDD 2005»
14 years 8 months ago
Summarizing itemset patterns: a profile-based approach
Frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. However, the bottleneck of...
Xifeng Yan, Hong Cheng, Jiawei Han, Dong Xin
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