We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Information analysis often involves decomposing data into sub-groups to allow for comparison and identification of relationships. Breakdown Visualization provides a mechanism to s...
This paper presents a method to infer hidden semantic cues by accumulating the knowledge learned from relevance feedback sessions. We propose to explicitly represent a semantic sp...
Direct volume rendering techniques map volumetric attributes (e.g., density, gradient magnitude, etc.) to visual styles. Commonly this mapping is specified by a transfer function. ...
Peter Rautek, Stefan Bruckner, M. Eduard Grölle...
An important issue in data mining is the recognition of complex dependencies between attributes. Past techniques for identifying attribute dependence include correlation coefficie...