Graph data are subject to uncertainties in many applications due to incompleteness and imprecision of data. Mining uncertain graph data is semantically different from and computat...
The recent investigation of privacy-preserving data mining has been motivated by the growing concern about the privacy of individuals when their data is stored, aggregated, and mi...
Zhiqiang Yang, Rebecca N. Wright, Hiranmayee Subra...
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access...
This paper reports an experiment aimed at generating synthetic test data for fraud detection in an IP based videoon-demand service. The data generation verifies a methodology pre...
Privacy models such as k-anonymity and -diversity typically offer an aggregate or scalar notion of the privacy property that holds collectively on the entire anonymized data set....