Preserving the privacy of individuals when data are shared for clustering is a complex problem. The challenge is how to protect the underlying data values subjected to clustering w...
Data uncertainty is ubiquitous in many real-world applications such as sensor/RFID data analysis. In this paper, we investigate uncertain data that exhibit local correlations, tha...
The collection of moving object data is becoming more and more common, and therefore there is an increasing need for the efficient analysis and knowledge extraction of these data ...
Alejandro A. Vaisman, Bart Kuijpers, Bart Moelans,...
Privacy-preserving data mining has concentrated on obtaining valid results when the input data is private. An extreme example is Secure Multiparty Computation-based methods, where...
Traditional databases store sets of relatively static records with no pre-defined notion of time, unless timestamp attributes are explicitly added. While this model adequately rep...