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dc.contributor.authorEpperson, Willen_US
dc.contributor.authorLee, Doris Jung-Linen_US
dc.contributor.authorWang, Leijieen_US
dc.contributor.authorAgarwal, Kunalen_US
dc.contributor.authorParameswaran, Aditya G.en_US
dc.contributor.authorMoritz, Dominiken_US
dc.contributor.authorPerer, Adamen_US
dc.contributor.editorBorgo, Ritaen_US
dc.contributor.editorMarai, G. Elisabetaen_US
dc.contributor.editorSchreck, Tobiasen_US
dc.date.accessioned2022-06-03T06:05:52Z
dc.date.available2022-06-03T06:05:52Z
dc.date.issued2022
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14529
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14529
dc.description.abstractExisting visualization recommendation systems commonly rely on a single snapshot of a dataset to suggest visualizations to users. However, exploratory data analysis involves a series of related interactions with a dataset over time rather than one-off analytical steps. We present Solas, a tool that tracks the history of a user's data analysis, models their interest in each column, and uses this information to provide visualization recommendations, all within the user's native analytical environment. Recommending with analysis history improves visualizations in three primary ways: task-specific visualizations use the provenance of data to provide sensible encodings for common analysis functions, aggregated history is used to rank visualizations by our model of a user's interest in each column, and column data types are inferred based on applied operations. We present a usage scenario and a user evaluation demonstrating how leveraging analysis history improves in situ visualization recommendations on real-world analysis tasks.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Human-centered computing --> Visualization; Visualization systems and tools
dc.subjectHuman centered computing
dc.subjectVisualization
dc.subjectVisualization systems and tools
dc.titleLeveraging Analysis History for Improved In Situ Visualization Recommendationen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersWorkflows and Parameters
dc.description.volume41
dc.description.number3
dc.identifier.doi10.1111/cgf.14529
dc.identifier.pages145-155
dc.identifier.pages11 pages


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  • 41-Issue 3
    EuroVis 2022 - Conference Proceedings

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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License