An ensemble is generated by training multiple component learners for a same task and then combining them for predictions. It is known that when lots of trained learners are availab...
In solving application problems, the data sets used to train a neural network may not be hundred percent precise but within certain ranges. Representing data sets with intervals, ...
This paper presents a partial solution to a component of the problem of lexical choice: choosing the synonym most typical, or expected, in context. We apply a new statistical appr...
We present an adaptation of constraint satisfaction inference (Canisius et al., 2006b) for predicting dependency trees. Three different classifiers are trained to predict weighte...
In this paper, we present a novel collaborative authoring tool that was designed to allow medical teachers to formalize and visualize their knowledge for medical intelligent tutor...
Siriwan Suebnukarn, Peter Haddawy, Phattanapon Rhi...