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Visual similarity matrices (VSMs) are a common technique for visualizing graphs and other types of relational data. While traditionally used for small data sets or well-ordered large data sets, they have recently become popular for visualizing large graphs. However, our experience with users has revealed that large VSMs are difficult to interpret. In this paper, we catalog common structural features...
In this study, we examine the use of graph ordering algorithms for visual analysis of data sets using visual similarity matrices. Visual similarity matrices display the relationships between data items in a dot-matrix plot format, with the axes labeled with the data items and points drawn if there is a relationship between two data items. The biggest challenge for displaying data using this representation...
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