Abstract. For a number of problems, such as ontology learning or image labeling, we need to handle uncertainty and inconsistencies in an appropriate way. Fuzzy and Probabilistic De...
Stefan Scheglmann, Carsten Saathoff, Steffen Staab
The deployment of learning resources on the web by different experts has resulted in the accessibility of multiple viewpoints about the same topics. In this work we assume that lea...
Various forms of reasoning, the profusion of knowledge, the gap between neuro-inspired approaches and conceptual representations, the problem of inconsistent data input, and the ma...
Abstract. The demonstration presents Pronto - a prototype of a nonmonotonic probabilistic reasoner for very expressive Description Logics. Pronto is built on top of the OWL DL reas...
This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling ...