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Graphemes : self-organizing shape-based clustered structures for network visualisations

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conference contribution
posted on 2011-02-04, 12:15 authored by Ross Shannon, Aaron Quigley, Paddy Nixon
Network visualisations use clustering approaches to simplify the presentation of complex graph structures. We present a novel application of clustering algorithms, which controls the visual arrangement of the vertices in a cluster to explicitly encode information about that cluster. Our technique arranges parts of the graph into symbolic shapes, depending on the relative size of each cluster. Early results suggest that this layout augmentation helps viewers make sense of a graph's scale and number of elements, while facilitating recall of graph features, and increasing stability in dynamic graph scenarios.

History

Publication

CHI EA '10 Proceedings of the 28th of the international conference extended abstracts on Human factors in computing systems;pp. 4195-4200

Publisher

Association for Computing Machinery

Note

peer-reviewed

Other Funding information

SFI

Language

English

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