Matthias Kreuseler

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This paper describes major concepts of a scalable information visualization framework. We assume that the exploration of hete-rogenous information spaces at arbitrary levels of detail requires a suitable preprocessing of information quantities, the combination of different graphical interfaces and the illustration of the frame of reference of given(More)
ÐThe exploration of heterogenous information spaces requires suitable mining methods as well as effective visual interfaces. Most of the existing systems concentrate either on mining algorithms or on visualization techniques. This paper describes a flexible framework for Visual Data Mining which combines analytical and visual methods to achieve a better(More)
A major challenge of current visualization and visual data mining (VDM) frameworks is to support users in the orientation in complex visual mining scenarios. An important aspect to increase user support and user orientation is to use a history mechanism that, first of all, provides un-and redoing functionality. In this paper, we present a new approach to(More)
This paper presents work in progress on our approach to visualizing multi-dimensional and hierarchical information. We propose two new graphical user interfaces, the Magic Eye View (MEV) and ShapeVis to explore information spaces. In order to cope with large information sets we combine MEV and ShapeVis with dynamic hierarchical clustering of information(More)
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