Context Visualization for Visual Data Mining
Visual Data Mining
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This paper presents a technique for navigating large clustered graphs with triple-layer display. Although our navigation and interaction technique can be applied independently to any graph layout algorithms, in our implementation, our navigation algorithm is cooperated with a clustered graph layout algorithm. In short, we provide users with the display of three levels of contextual information for navigation. They are the display of full-context, the display of the current-context view and the display of the focused view. Our technique not only allows users to navigate hierarchically up and down through the entire clustered graph, but also provides a way to navigate multiple clusters concurrently. We also use animation to preserve the users' mental maps during the interaction.