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    Combining the Automated Segmentation and Visual Analysis of Multivariate Time Series

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    Date
    2018
    Author
    Bernard, Jürgen ORCID
    Bors, Christian ORCID
    Bögl, Markus
    Eichner, Christian
    Gschwandtner, Theresia ORCID
    Miksch, Silvia ORCID
    Schumann, Heidrun
    Kohlhammer, Jörn
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    Abstract
    For the automatic segmentation of multivariate time series domain experts at first need to consider a huge space of alternative configurations of algorithms and parameters. We assume that only a small subset of these configurations needs to be computed and analyzed to lead users to meaningful configurations. To expedite this search, we propose the conceptualization of a segmentation workflow. First, with an algorithmic segmentation pipeline, domain experts can calculate segmentation results with different parameter configurations. Second, in an interactive visual analysis step, domain experts can explore segmentation results to further adapt and improve segmentation pipeline in an informed way. In the interactive analysis approach influences of algorithms, parameters, and different types of uncertainty information are conveyed, which is decisive to trigger selective and purposeful re-calculations. The workflow is built upon reflections on collaborations with domain experts working in activity recognition, which also defines our usage scenario demonstrating the applicability of the workflow.
    BibTeX
    @inproceedings {10.2312:eurova.20181112,
    booktitle = {EuroVis Workshop on Visual Analytics (EuroVA)},
    editor = {Christian Tominski and Tatiana von Landesberger},
    title = {{Combining the Automated Segmentation and Visual Analysis of Multivariate Time Series}},
    author = {Bernard, Jürgen and Bors, Christian and Bögl, Markus and Eichner, Christian and Gschwandtner, Theresia and Miksch, Silvia and Schumann, Heidrun and Kohlhammer, Jörn},
    year = {2018},
    publisher = {The Eurographics Association},
    ISBN = {978-3-03868-064-2},
    DOI = {10.2312/eurova.20181112}
    }
    URI
    http://dx.doi.org/10.2312/eurova.20181112
    https://diglib.eg.org:443/handle/10.2312/eurova20181112
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    Eurographics Association copyright © 2013 - 2022 
    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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