Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction

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dc.contributor.authorBögl, Markusen_US
dc.contributor.authorFilzmoser, Peteren_US
dc.contributor.authorGschwandtner, Theresiaen_US
dc.contributor.authorLammarsch, Timen_US
dc.contributor.authorLeite, Roger A.en_US
dc.contributor.authorMiksch, Silviaen_US
dc.contributor.authorRind, Alexanderen_US
dc.contributor.editorHeer, Jeffrey and Ropinski, Timo and van Wijk, Jarkeen_US
dc.date.accessioned2017-06-12T05:22:35Z
dc.date.available2017-06-12T05:22:35Z
dc.date.issued2017
dc.description.abstractThe cycle plot is an established and effective visualization technique for identifying and comprehending patterns in periodic time series, like trends and seasonal cycles. It also allows to visually identify and contextualize extreme values and outliers from a different perspective. Unfortunately, it is limited to univariate data. For multivariate time series, patterns that exist across several dimensions are much harder or impossible to explore. We propose a modified cycle plot using a distance-based abstraction (Mahalanobis distance) to reduce multiple dimensions to one overview dimension and retain a representation similar to the original. Utilizing this distance-based cycle plot in an interactive exploration environment, we enhance the Visual Analytics capacity of cycle plots for multivariate outlier detection. To enable interactive exploration and interpretation of outliers, we employ coordinated multiple views that juxtapose a distance-based cycle plot with Cleveland's original cycle plots of the underlying dimensions. With our approach it is possible to judge the outlyingness regarding the seasonal cycle in multivariate periodic time series.en_US
dc.description.number3
dc.description.sectionheadersText and Time Visualization
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume36
dc.identifier.doi10.1111/cgf.13182
dc.identifier.issn1467-8659
dc.identifier.pages227-238
dc.identifier.urihttps://doi.org/10.1111/cgf.13182
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13182
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectMathematics of Computing [G.3]
dc.subjectProbability and Statistics
dc.subjectTime Series Analysis
dc.subjectInformation Interfaces and Presentation [H.5.2]
dc.subjectUser Interfaces
dc.subjectGraphical user interfaces
dc.titleCycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstractionen_US
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