The bottleneck of a data warehouse implementation is the ETL (extraction, transformation, and load) process, which carries out the initial population of the data warehouse and its...
Mixture models, such as Gaussian Mixture Model, have been widely used in many applications for modeling data. Gaussian mixture model (GMM) assumes that data points are generated fr...
We propose a novel approach for statistical risk modeling of network attacks that lets an operator perform risk analysis using a data model and an impact model on top of an attack ...
The convergence of embedded sensor systems and stream query processing suggests an important role for database techniques, in managing data that only partially – and often inacc...
Eirinaios Michelakis, Daisy Zhe Wang, Minos N. Gar...
Abstract Traditional financial analysis systems utilize lowlevel price data as their analytical basis. For example, a decision-making system for stock predictions regards raw price...