The desire to predict power generation at a given point in time is essential to power scheduling, energy trading, and availability modeling. The research conducted within is conce...
—Knowledge discovery from scientific articles has received increasing attentions recently since huge repositories are made available by the development of the Internet and digit...
This paper addresses the training of classification trees for weakly labelled data. We call ”weakly labelled data”, a training set such as the prior labelling information pro...
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...