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dc.contributor.authorChen, Chenen_US
dc.contributor.authorLiu, Zhichengen_US
dc.contributor.editorBruckner, Stefanen_US
dc.contributor.editorRaidou, Renata G.en_US
dc.contributor.editorTurkay, Cagatayen_US
dc.date.accessioned2023-06-10T06:28:20Z
dc.date.available2023-06-10T06:28:20Z
dc.date.issued2023
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14855
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14855
dc.description.abstractWe present a state-of-the-art report on visualization corpora in automated chart analysis research. We survey 56 papers that created or used a visualization corpus as the input of their research techniques or systems. Based on a multi-level task taxonomy that identifies the goal, method, and outputs of automated chart analysis, we examine the property space of existing chart corpora along five dimensions: format, scope, collection method, annotations, and diversity. Through the survey, we summarize common patterns and practices of creating chart corpora, identify research gaps and opportunities, and discuss the desired properties of future benchmark corpora and the required tools to create them.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies -> Machine learning; Human-centered computing -> Visualization
dc.subjectComputing methodologies
dc.subjectMachine learning
dc.subjectHuman centered computing
dc.subjectVisualization
dc.titleThe State of the Art in Creating Visualization Corpora for Automated Chart Analysisen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersParameter Spaces and Chart Corpora
dc.description.volume42
dc.description.number3
dc.identifier.doi10.1111/cgf.14855
dc.identifier.pages449-470
dc.identifier.pages22 pages
dc.description.documenttypestar


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