Frank Rügheimer

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Graphical models provide a compact approach to analysing and modeling the interaction between attributes. By exploiting marginal and conditional independence relations, high-dimensional distributions are factorized into a set of distributions over lower dimensional subdomains, allowing for a compact representation and efficient reasoning. In this paper, we(More)
MOTIVATION Research on methods for the inference of networks from biological data is making significant advances, but the adoption of network inference in biomedical research practice is lagging behind. Here, we present Cyni, an open-source 'fill-in-the-algorithm' framework that provides common network inference functionality and user interface elements.(More)
In this work, we present and evaluate a new approach to semantic search. This approach is distinguished by pointing users to semantic concepts that offer possible refinements of their query. In parallel a combination of information retieval and machine learning strategies is applied to annotate and filter documents with respect to those semantic categories.(More)
With the widespread use of annotations in biological databases efficient models for statistical properties of set-valued attributes become increasingly relevant. In this work we introduce condensed random sets (CRS) as compact representations of distributions over annotation sets. The approach is discussed for both unorganized term vocabularies and term(More)
— A significant number of scientific and economic problems is characterised by a large number of interrelated variables. But with larger variable number, the domain under consideration may grow fast, so that analyses and reasoning become increasingly difficult. Graphical models allow to represent the combined distributions compactly and are suitable for(More)
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