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    Dual Adjacency Matrix: Exploring Link Groups in Dense Networks

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    Date
    2015
    Author
    Dinkla, Kasper
    Henry-Riche, Nathalie
    Westenberg, Michel A. ORCID
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    Abstract
    Node grouping is a common way of adding structure and information to networks that aids their interpretation. However, certain networks benefit from the grouping of links instead of nodes. Link communities, for example, are a form of link groups that describe high-quality overlapping node communities. There is a conceptual gap between node groups and link groups that poses an interesting visualization challenge. We introduce the Dual Adjacency Matrix to bridge this gap. This matrix combines node and link group techniques via a generalization that also enables it to be coordinated with a node-link-contour diagram. These methods have been implemented in a prototype that we evaluated with an information scientist and neuroscientist via interviews and prototype walk- throughs. We demonstrate this prototype with the analysis of a trade network and an fMRI correlation network.
    BibTeX
    @article {10.1111:cgf.12643,
    journal = {Computer Graphics Forum},
    title = {{Dual Adjacency Matrix: Exploring Link Groups in Dense Networks}},
    author = {Dinkla, Kasper and Henry-Riche, Nathalie and Westenberg, Michel A.},
    year = {2015},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    DOI = {10.1111/cgf.12643}
    }
    URI
    http://dx.doi.org/10.1111/cgf.12643
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    • 34-Issue 3
    • EuroVis15: Eurographics Conference on Visualization

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    Eurographics Association copyright © 2013 - 2022 
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    Theme by @mire NV
    System hosted at  Graz University of Technology.
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