Browsing by Author "Krause, Cedric"

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    Visually Abstracting Event Sequences as Double Trees Enriched with Category‐Based Comparison
    (© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Krause, Cedric; Agarwal, Shivam; Burch, Michael; Beck, Fabian; Hauser, Helwig and Alliez, Pierre
    Event sequence visualization aids analysts in many domains to better understand and infer new insights from event data. Analysing behaviour before or after a certain event of interest is a common task in many scenarios. In this paper, we introduce, formally define, and position as a domain‐agnostic tree visualization approach for this task. The visualization shows the sequences that led to the event of interest as a tree on the left, and those that followed on the right. Moreover, our approach enables users to create selections based on event attributes to interactively compare the events and sequences along colour‐coded categories. We integrate the double tree and category‐based comparison into a user interface for event sequence analysis. In three application examples, we show a diverse set of scenarios, covering short and long time spans, non‐spatial and spatial events, human and artificial actors, to demonstrate the general applicability of the approach.
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    Visually Analyzing Topic Change Points in Temporal Text Collections
    (The Eurographics Association, 2023) Krause, Cedric; Rieger, Jonas; Flossdorf, Jonathan; Jentsch, Carsten; Beck, Fabian; Guthe, Michael; Grosch, Thorsten
    Texts are collected over time and reflect temporal changes in the themes that they cover. While some changes might slowly evolve, other changes abruptly surface as explicit change points. In an application study for a change point extraction method based on a rolling Latent Dirichlet Allocation (LDA), we have developed a visualization approach that allows exploring such change points and related change patterns. Our visualization not only provides an overview of topics, but supports the detailed exploration of temporal developments. The interplay of general topic contents, development, and similarities with detected change points reveals rich insights into different kinds of change patterns. The approach comprises a combination of views including topic timeline representations with detected change points, comparative word clouds, and temporal similarity matrices. In an interactive exploration, these views adapt to selected topics, words, or points in time. We demonstrate the use cases of our approach in an in-depth application example involving statisticians.
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    Visually Explaining Publication Ranks in Citation-based Literature Search with PURE Suggest
    (The Eurographics Association, 2022) Beck, Fabian; Krause, Cedric; Krone, Michael; Lenti, Simone; Schmidt, Johanna
    Tracing citation links helps retrieve related publications. While most tools only allow the user to follow the citations of a single publication, some approaches support jointly analyzing the citations of a set of publications. Along similar lines, PURE suggest provides a detailed visual explanation of the ranking of suggested publications. The ranking is based on a score that combines citation numbers with keyword matching and is shown as a glyph for each publication. A citation network component references this glyph and visually embeds it into a timeline and cluster visualization.