TaskVis: Task-oriented Visualization Recommendation

dc.contributor.authorShen, Leixianen_US
dc.contributor.authorShen, Enyaen_US
dc.contributor.authorTai, Zhiweien_US
dc.contributor.authorSong, Yiranen_US
dc.contributor.authorWang, Jianminen_US
dc.contributor.editorAgus, Marco and Garth, Christoph and Kerren, Andreasen_US
dc.date.accessioned2021-06-12T11:03:37Z
dc.date.available2021-06-12T11:03:37Z
dc.date.issued2021
dc.description.abstractGeneral visualization recommendation systems typically make design decisions of the dataset automatically. However, these systems are only able to prune meaningless visualizations but fail to recommend targeted results. In this paper, we contributed TaskVis, a task-oriented visualization recommendation approach with detailed modeling of the user's analysis task. We first summarized a task base with 18 analysis tasks by a survey both in academia and industry. On this basis, we further maintained a rule base, which extends empirical wisdom with our targeted modeling of analysis tasks. Inspired by Draco, we enumerated candidate visualizations through answer set programming. After visualization generation, TaskVis supports four ranking schemes according to the complexity of charts, coverage of the user's interested columns and tasks. In two user studies, we found that TaskVis can well reflect the user's preferences and strike a great balance between automation and the user's intent.en_US
dc.description.sectionheadersInformation Visualization
dc.description.seriesinformationEuroVis 2021 - Short Papers
dc.identifier.doi10.2312/evs.20211061
dc.identifier.isbn978-3-03868-143-4
dc.identifier.pages91-95
dc.identifier.urihttps://doi.org/10.2312/evs.20211061
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evs20211061
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectInformation visualization
dc.subjectInformation Systems
dc.subjectData analytics
dc.titleTaskVis: Task-oriented Visualization Recommendationen_US
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