Embedding, Clustering and Coloring for Dynamic Maps (Long System Demo)

We describe a practical approach for visualizing dynamic relational data and multiple relationships on the same data using a geographic map metaphor, where clusters of nodes form countries and neighboring countries correspond to nearby clusters. Our aim is to compare two or more maps obtained using different similarity metrics and to provide an interactive tool to visually explore the effect of combining two or more similarity metrics. Our method ensures good readability and mental map preservation, based on dynamic node placement with node stability, dynamic clustering with cluster stability, and dynamic coloring with color stability.