We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
Properly addressing the discretization process of continuos valued features is an important problem during decision tree learning. This paper describes four multi-interval discreti...
In opinion mining of product reviews, one often wants to produce a summary of opinions based on product features/attributes. However, for the same feature, people can express it w...
Context can be seen as a paradigm aiming to improve user interaction with software. For Web applications in particular, the issues of content explosion and technological constrain...
This work presents a mesh refinement indicator based on entropy variables, with an application to the compressible Navier-Stokes equations. The entropy variables are shown to sati...