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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
ICDM
2010
IEEE
115views Data Mining» more  ICDM 2010»
13 years 5 months ago
Polishing the Right Apple: Anytime Classification Also Benefits Data Streams with Constant Arrival Times
Classification of items taken from data streams requires algorithms that operate in time sensitive and computationally constrained environments. Often, the available time for class...
Jin Shieh, Eamonn J. Keogh
PAKDD
2004
ACM
97views Data Mining» more  PAKDD 2004»
14 years 28 days ago
Further Applications of a Particle Visualization Framework
Our previous work introduced a 3D particle visualization framework that viewed each data point as being a particle affected by gravitational forces. We showed the use of this tool ...
Ke Yin, Ian Davidson
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
EDBT
2009
ACM
90views Database» more  EDBT 2009»
14 years 2 months ago
Privacy-preserving data mashup
Mashup is a web technology that combines information from more than one source into a single web application. This technique provides a new platform for different data providers ...
Noman Mohammed, Benjamin C. M. Fung, Ke Wang, Patr...