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» A Clustering Approach for Achieving Data Privacy
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DMIN
2009
222views Data Mining» more  DMIN 2009»
13 years 5 months ago
P-Sensitive K-Anonymity for Social Networks
-- The proliferation of social networks, where individuals share private information, has caused, in the last few years, a growth in the volume of sensitive data being stored in th...
Roy Ford, Traian Marius Truta, Alina Campan
VLDB
1994
ACM
121views Database» more  VLDB 1994»
13 years 11 months ago
The Impact of Global Clustering on Spatial Database Systems
Global clustering has rarely been investigated in the area of spatial database systems although dramatic performance improvements can be achieved by using suitable techniques. In ...
Thomas Brinkhoff, Hans-Peter Kriegel
KDD
2008
ACM
140views Data Mining» more  KDD 2008»
14 years 7 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang
EUROPAR
2003
Springer
14 years 18 days ago
Distributed Application Monitoring for Clustered SMP Architectures
Abstract. Performance analysis for terascale computing requires a combination of new concepts including distribution, on-line processing and automation. As a foundation for tools r...
Karl Fürlinger, Michael Gerndt
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
14 years 7 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...