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KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 9 months ago
Privacy-Preserving Data Mining through Knowledge Model Sharing
Privacy-preserving data mining (PPDM) is an important topic to both industry and academia. In general there are two approaches to tackling PPDM, one is statistics-based and the oth...
Patrick Sharkey, Hongwei Tian, Weining Zhang, Shou...
KDD
2006
ACM
128views Data Mining» more  KDD 2006»
14 years 9 months ago
On privacy preservation against adversarial data mining
Privacy preserving data processing has become an important topic recently because of advances in hardware technology which have lead to widespread proliferation of demographic and...
Charu C. Aggarwal, Jian Pei, Bo Zhang 0002
SDMW
2004
Springer
14 years 2 months ago
Experimental Analysis of Privacy-Preserving Statistics Computation
The recent investigation of privacy-preserving data mining and other kinds of privacy-preserving distributed computation has been motivated by the growing concern about the privacy...
Hiranmayee Subramaniam, Rebecca N. Wright, Zhiqian...
FQAS
2006
Springer
99views Database» more  FQAS 2006»
14 years 19 days ago
Partition-Based Approach to Processing Batches of Frequent Itemset Queries
We consider the problem of optimizing processing of batches of frequent itemset queries. The problem is a particular case of multiple-query optimization, where the goal is to minim...
Przemyslaw Grudzinski, Marek Wojciechowski, Maciej...
ICDM
2005
IEEE
139views Data Mining» more  ICDM 2005»
14 years 2 months ago
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
Yongge Wang, Xintao Wu