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Visual Analysis of Large Graphs Using (X,Y)Clustering and Hybrid Visualizations

Visual Analysis of Large Graphs Using (X,Y)Clustering and Hybrid Visualizations,10.1109/TVCG.2010.265,IEEE Transactions on Visualization and Computer

Visual Analysis of Large Graphs Using (X,Y)Clustering and Hybrid Visualizations  
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Many different approaches have been proposed for the challenging problem of visually analyzing large networks. Clustering is one of the most promising. In this paper, we propose a new clustering technique whose goal is that of producing both intracluster graphs and intercluster graph with desired topological properties. We formalize this concept in the ðX; Y Þ-clustering framework, where Y is the class that defines the desired topological properties of intracluster graphs and X is the class that defines the desired topological properties of the intercluster graph. By exploiting this approach, hybrid visualization tools can effectively combine different node-link and matrix-based representations, allowing users to interactively explore the graph by expansion/contraction of clusters without loosing their mental map. As a proof of concept, we describe the system Visual Hybrid (X,Y)-clustering (VHYXY) that implements our approach and we present the results of case studies to the visual analysis of social networks.
Journal: IEEE Transactions on Visualization and Computer Graphics - TVCG , vol. 17, no. 11, pp. 1587-1598, 2011
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