Bayesian networks (BN) are particularly well suited to capturing vague and uncertain knowledge. However, the capture of this knowledge and associated reasoning from human domain e...
Jonathan D. Pfautz, Zach Cox, Geoffrey Catto, Davi...
In this paper we introduce the design and development of the Learning Cube as a novel tangible learning appliance. Using the common shape of a cube we implemented a general learnin...
Lucia Terrenghi, Matthias Kranz, Paul Holleis, Alb...
Current skyline evaluation techniques assume a fixed ordering on the attributes. However, dynamic preferences on nominal attributes are more realistic in known applications. In or...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu, Jian Pei, ...
The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...
In this paper we propose a new technique to enhance emotion recognition by combining in different ways what we call emotion predictions. The technique is called F2 as the combinat...