Visually Abstracting Event Sequences as Double Trees Enriched with Category‐Based Comparison

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dc.contributor.authorKrause, Cedricen_US
dc.contributor.authorAgarwal, Shivamen_US
dc.contributor.authorBurch, Michaelen_US
dc.contributor.authorBeck, Fabianen_US
dc.contributor.editorHauser, Helwig and Alliez, Pierreen_US
dc.date.accessioned2023-10-06T11:58:50Z
dc.date.available2023-10-06T11:58:50Z
dc.date.issued2023
dc.description.abstractEvent 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.en_US
dc.description.number6
dc.description.sectionheadersORIGINAL ARTICLES
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14805
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14805
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14805
dc.publisher© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectVisualization
dc.subjectInformation Visualization
dc.titleVisually Abstracting Event Sequences as Double Trees Enriched with Category‐Based Comparisonen_US
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