Anomaly detection systems largely depend on user profile data to be able to detect deviation from normal activity. Most of this profile data is based on commands executed by use...
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
We propose an approach for the selective enforcement of access control restrictions in, possibly distributed, large data collections based on two basic concepts: i) flexible autho...
Sabrina De Capitani di Vimercati, Sara Foresti, Su...
s the Pus using the OpenCL API as the platform independent programming model. It has the proposal to extend OpenCL with a module that schedule and balance the workload over the CPU...