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Graphemes: self-organizing shape-based clustered structures for network visualisations
conference contribution
posted on 2023-05-24, 10:16 authored by Shannon, R, Quigley, AJ, Nixon, PANetwork 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 title
Proceedings of the 28th International conference on Human factors in computing systemsEditors
E Mynatt, D Schoner, G Fitzpatrick, St Hudson, K Edwards, T RoddenPagination
4195-4200ISBN
978-1-60558-930-5Department/School
School of Information and Communication TechnologyPublisher
ACM Digital LibraryPlace of publication
New York, USAEvent title
International conference on Human factors in computing systemsEvent Venue
Atlanta, GA, USADate of Event (Start Date)
2010-04-10Date of Event (End Date)
2010-04-15Repository Status
- Restricted