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» Output privacy in data mining
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ICDE
2007
IEEE
165views Database» more  ICDE 2007»
15 years 11 months ago
On Randomization, Public Information and the Curse of Dimensionality
A key method for privacy preserving data mining is that of randomization. Unlike k-anonymity, this technique does not include public information in the underlying assumptions. In ...
Charu C. Aggarwal
ICDM
2003
IEEE
92views Data Mining» more  ICDM 2003»
15 years 3 months ago
Postprocessing Decision Trees to Extract Actionable Knowledge
Most data mining algorithms and tools stop at discovered customer models, producing distribution information on customer profiles. Such techniques, when applied to industrial pro...
Qiang Yang, Jie Yin, Charles X. Ling, Tielin Chen
PODS
2005
ACM
96views Database» more  PODS 2005»
15 years 10 months ago
Privacy-enhancing k-anonymization of customer data
In order to protect individuals' privacy, the technique of kanonymization has been proposed to de-associate sensitive attributes from the corresponding identifiers. In this p...
Sheng Zhong, Zhiqiang Yang, Rebecca N. Wright
AISADM
2005
Springer
15 years 3 months ago
An Architecture for Distributed Agent-Based Data Preprocessing
Advances in agent technologies have fueled interest towards combining agent-based techniques with tools from data mining. Furthermore, the advent of the ubiquitous computing paradi...
Petteri Nurmi, Michael Przybilski, Greger Lind&eac...
ISI
2007
Springer
15 years 4 months ago
Mining Higher-Order Association Rules from Distributed Named Entity Databases
The burgeoning amount of textual data in distributed sources combined with the obstacles involved in creating and maintaining central repositories motivates the need for effective ...
Shenzhi Li, Christopher D. Janneck, Aditya P. Bela...