Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDM...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
Abstract. In this paper, we present a new ontology-based formalism for representing patent information. The framework defines concepts and relations for the major aspects of paten...
Mark Giereth, Steffen Koch, Yiannis Kompatsiaris, ...
In this paper we describe a method for performing word sense disambiguation (WSD). The method relies on unsupervised learning and exploits functional relations among words as prod...
We describe an application of the BOXES learning algorithm of Michie and Chambers (1968) to a large-scale, real-world problem, namely, learning to control a steel mill. By applyin...
Michael McGarity, Claude Sammut, David P. Clements
This paper presents a method for updating approximations of a concept incrementally. The results can be used to implement a quasi-incremental algorithm for learning classification...