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    Supporting Visual Parameter Analysis of Time Series Segmentation with Correlation Calculations (Unknown language)

    In: EuroVis 2018 - Posters ; 37-39  ; 2018

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    Parameter analysis can be used to find out how individual parameters influence the output of an algorithm. We aim to support the visual parameter analysis of algorithms for the segmentation of time series. To this end, we automatically search for correlations between parameters and the segmentation outputs. Correlations are not only determined globally, but also locally within parameter subspaces. Calculated correlations are used to visually emphasize parameter and value ranges with high influence on the segmentation. By interactive exploration, the analyst can study the multidimensional parameter space in depth.

    Table of contents conference proceedings

    The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.

    1
    CV3: Visual Exploration, Assessment, and Comparison of CVs
    Filipov, Velitchko Andreev / Federico, Paolo / Miksch, Silvia et al. | 2018
    5
    Extending Document Exploration with Image Retrieval: Concept and First Results
    Shao, Lin / Glatz, Mathias / Gergely, Eric / Müller, Markus / Munter, Denis / Papst, Stefan / Schreck, Tobias et al. | 2018
    9
    Visually Exploring Data Provenance and Quality of Open Data
    Bors, Christian / Gschwandtner, Theresia / Miksch, Silvia et al. | 2018
    13
    Case Studies of Shareable Personal Map Visualization
    Ruchikachorn, Puripant et al. | 2018
    17
    An Eye-Tracking Study on Sparklines within Textual Context
    Ruchikachorn, Puripant / Rattanawicha, Pimmanee et al. | 2018
    21
    Network Analysis for Financial Fraud Detection
    Leite, Roger A. / Gschwandtner, Theresia / Miksch, Silvia / Gstrein, Erich / Kuntner, Johannes et al. | 2018
    25
    Validation of Quantitative Measures for Edge Bundling by Comparing with Human Feeling
    Saga, Ryosuke et al. | 2018
    29
    ViMEC: Interactive Application for Micro-Cluster Visualizations
    Schmidt, Florian / Ehrenfeld, Yannick et al. | 2018
    33
    Exploring Uncertainty in Image Segmentation Ensembles
    Fröhler, Bernhard / Möller, Torsten / Weissenböck, Johannes / Hege, Hans-Christian / Kastner, Johann / Heinzl, Christoph et al. | 2018
    37
    Supporting Visual Parameter Analysis of Time Series Segmentation with Correlation Calculations
    Eichner, Christian / Schumann, Heidrun / Tominski, Christian et al. | 2018
    41
    The Impact of Visualizing Uncertainty on Train Trip Selection
    Wunderlich, Marcel / Ballweg, Kathrin / Landesberger, Tatiana von et al. | 2018
    45
    Categorizing Uncertainties in the Process of Segmenting and Labeling Time Series Data
    Bögl, Markus / Bors, Christian / Gschwandtner, Theresia / Miksch, Silvia et al. | 2018
    49
    Visual Analysis of Sentiment and Stance in Social Media Texts
    Kucher, Kostiantyn / Paradis, Carita / Kerren, Andreas et al. | 2018
    53
    Towards Natural Language Empowered Interactive Data Analysis
    Turkay, Cagatay / Henkin, Rafael et al. | 2018
    57
    A Visual Comparison of Hand-Drawn and Machine-Generated Human Metabolic Pathways
    Wu, Hsiang-Yun / Nöllenburg, Martin / Viola, Ivan et al. | 2018

    How to get this title?

    Check access
    Download
    Commercial Copyright fee: €14.50 Basic fee: €4.00 Total price: €18.50
    Academic Copyright fee: €4.50 Basic fee: €2.00 Total price: €6.50

    Export, share and cite

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