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KDD
2007
ACM
152views Data Mining» more  KDD 2007»
14 years 5 months ago
Privacy-Preserving Sharing of Horizontally-Distributed Private Data for Constructing Accurate Classifiers
Data mining tasks such as supervised classification can often benefit from a large training dataset. However, in many application domains, privacy concerns can hinder the construc...
Vincent Yan Fu Tan, See-Kiong Ng
ICDM
2005
IEEE
153views Data Mining» more  ICDM 2005»
13 years 10 months ago
Privacy-Preserving Frequent Pattern Mining across Private Databases
Privacy consideration has much significance in the application of data mining. It is very important that the privacy of individual parties will not be exposed when data mining te...
Ada Wai-Chee Fu, Raymond Chi-Wing Wong, Ke Wang
KDD
2004
ACM
159views Data Mining» more  KDD 2004»
13 years 10 months ago
Optimal randomization for privacy preserving data mining
Randomization is an economical and efficient approach for privacy preserving data mining (PPDM). In order to guarantee the performance of data mining and the protection of individ...
Michael Yu Zhu, Lei Liu
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 5 months ago
Privacy preserving regression modelling via distributed computation
Reluctance of data owners to share their possibly confidential or proprietary data with others who own related databases is a serious impediment to conducting a mutually beneficia...
Ashish P. Sanil, Alan F. Karr, Xiaodong Lin, Jerom...
SIGMOD
2010
ACM
243views Database» more  SIGMOD 2010»
13 years 5 months ago
Non-homogeneous generalization in privacy preserving data publishing
Most previous research on privacy-preserving data publishing, based on the k-anonymity model, has followed the simplistic approach of homogeneously giving the same generalized val...
Wai Kit Wong, Nikos Mamoulis, David Wai-Lok Cheung