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Interactive Visualization of Continuous Node Features in Graphs

Interactive Visualization of Continuous Node Features in Graphs

This video was recorded at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Bled 2009. Ordinary graphs only support discrete structures. In this paper we present an approach towards embedding continuous data – like time stamps or series of measurements – in discrete graph models. These continuous meta-information implicitly define relations between vertices which are not explicitly defined in the graph itself. We call this an induced Non-Discrete Graph Structure (NoDeS). The model is helpful for visualization of time-dependent models or values from physical domains. We provide a formal definition of NoDeS based on graphs and two mappings, instance and annotation based, to already known graph structures and visualizations. A visualization of multi-partite projection provides a representation of information from several contexts, enabling NoDeS for a generic context switching mechanism which is used for interaction with these structures. Finally, we introduce an application concept for agent-driven event scheduling using NoDeS.


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