Traditional Machine Learning approaches based on single inference mechanisms have reached their limits. This causes the need for a framework that integrates approaches based on aba...
Abstract. In this paper we discuss the automatic construction of webbased courseware applications from XML descriptions of appropriate UML models. The created applications conform ...
Andreas Papasalouros, Symeon Retalis, Nikolaos Pap...
Abstract. We investigate the generalization behavior of sequential prediction (online) algorithms, when data are generated from a probability distribution. Using some newly develop...
Abstract. We present a simple and extendible framework to collect attention metadata and store them for further analysis. Currently, several metadata collectors have been implement...
Maren Scheffel, Martin Friedrich, Katja Niemann, U...
Abstract Relational rule learning algorithms are typically designed to construct classification and prediction rules. However, relational rule learning can be adapted also to subgr...