CAVIR: Correspondence Analysis in Virtual Reality

Andrea Bönsch, Frederik Graff, Daniel Bündgens, Torsten Wolfgang Kuhlen
Virtuelle und Erweiterte Realität, 9. Workshop der GI-Fachgruppe VR/AR (2012)

Correspondence Analysis (CA) is used to interpret correlations between categorical variables in the areas of social science and market research. To do so, coherences of variables are converted to a three-dimensional point cloud and plotted as several different 2D-mappings, each containing two axes. The major challenge is to correctly interpret these plottings. Due to a missing axis, distances can easily be under- or overestimated. This can lead to a misinterpretation and thus a misclustering of data. To address this problem we present CAVIR, an approach for CA in Virtual Reality. It supports users with a three-dimensional representation of the point cloud and different options to show additional information, to measure Euclidean distances, and to cluster points. Besides, the motion parallax and a free rotation of the entire point cloud enable the CA expert to always have a correct view of the data.

Best Presentation Award!

» Show BibTeX

Title = {{CAVIR}: {C}orrespondence {A}nalysis in {V}irtual {R}eality},
Author = {Andrea B\"{o}nsch and Frederik Graff and Daniel B\"{u}ndgens and Torsten Kuhlen},
Journal = {{V}irtuelle und {E}rweiterte {R}ealit\"at, 9. {W}orkshop der {GI}-{F}achgruppe {VR}/{AR}},
Year = {2012},
Pages = {49-60},
ISSN = {978-3-8440-1309-2}
Publisher = {Shaker Verlag},

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