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    Stress Maps: Analysing Local Phenomena in Dimensionality Reduction Based Visualisations

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    013-018.pdf (419.2Kb)
    Date
    2010
    Author
    Seifert, Christin
    Sabol, Vedran
    Kienreich, Wolfgang
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    Abstract
    Challenges in Visual Analytics frequently involve massive repositories, which do not only contain a large number of information artefacts, but also a high number of relevant dimensions per artefact. Dimensionality reduction algorithms are commonly used to transform high-dimensional data into low- dimensional representations which are suitable for visualisation purposes. For example, Information Landscapes visualise high-dimensional data in two dimensions using distance-preserving projection methods. The inaccuracies introduced by such methods are usually expressed through a global stress measure which does not provide insight into localised phenomena. In this paper, we propose the use of Stress Maps, a combination of heat maps and information landscapes, to support algorithm development and optimization based on local stress measures. We report on an application of Stress Maps to a scalable text projection algorithm and describe two categories of problems related to localised stress phenomena which we have identified using the proposed method.
    BibTeX
    @inproceedings {PE:EuroVAST:EuroVAST10:013-018,
    booktitle = {EuroVAST 2010: International Symposium on Visual Analytics Science and Technology},
    editor = {Joern Kohlhammer and Daniel Keim},
    title = {{Stress Maps: Analysing Local Phenomena in Dimensionality Reduction Based Visualisations}},
    author = {Seifert, Christin and Sabol, Vedran and Kienreich, Wolfgang},
    year = {2010},
    publisher = {The Eurographics Association},
    ISBN = {978-3-905673-74-6},
    DOI = {10.2312/PE/EuroVAST/EuroVAST10/013-018}
    }
    URI
    http://dx.doi.org/10.2312/PE/EuroVAST/EuroVAST10/013-018
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    Eurographics Association copyright © 2013 - 2020 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
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