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Abstract: Visual data mining has been established to e#ectively analyze large, complex numerical data sets. Especially, the extraction and visualization of inherent structures such as hierarchies and networks has made a significant leap forward. However, it is still a challenging task for users to explore explicitly given large structures. In this paper, we approach this task by tightly coupling visualization and graph-theoretical methods. Therefore, we investigate if and how visualization can benefit... (Update)
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BibTeX entry: (Update)
@misc{ schulz-framework,
author = "Hans-Jörg Schulz and Thomas Nocke and Heidrun Schumann",
title = "A Framework for Visual Data Mining of Structures",
url = "citeseer.ist.psu.edu/744089.html" }
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