The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
Acquiring knowledge from the Web to build domain ontologies has become a common practice in the Ontological Engineering field. The vast amount of freely available information allo...
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
The computer aided diagnosis (CAD) problems of detecting
potentially diseased structures from medical images are
typically distinguished by the following challenging characterist...
Joining up services in e-Government usually implies governmental agencies acting in concert without a central control regime. This requires to the sharing scattered and heterogeneo...
Alessio Gugliotta, John Domingue, Liliana Cabral, ...