Determining the size of an ontology that is automatically learned from texts is an open issue. In this paper, we study the similarity between ontology concepts at different levels ...
Elias Zavitsanos, Sergios Petridis, Georgios Palio...
Due to the scale and computational complexity of current simulation codes, metamodels (or surrogate models) have become indispensable tools for exploring and understanding the desi...
The analysis of spectral data constitutes new challenges for machine learning algorithms due to the functional nature of the data. Special attention is paid to the metric used in t...
Petra Schneider, Frank-Michael Schleif, Thomas Vil...
This paper proposes a novel approach to modeling the diversity in users’ perceptions, based on a mixture of qualitative and quantitative techniques: the Repertory Grid Technique ...
Extensive labeled data for image annotation systems, which learn to assign class labels to image regions, is difficult to obtain. We explore a hybrid model framework for utilizing...