Analyzing the role of dimension arrangement for data visualization in radviz
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Interactive visual analysis of temporal cluster structures
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Integrating cluster formation and cluster evaluation in interactive visual analysis
Proceedings of the 27th Spring Conference on Computer Graphics
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Radviz is a radial visualization with dimensions assigned to points called dimensional anchors (DAs) placed on the circumference of a circle. Records are assigned locations within the circle as a function of its relative attraction to each of the DAs. The DAs can be moved either interactively or algorithmically to reveal different meaningful patterns in the dataset. In this paper we describe Vectorized Radviz (VRV) which extends the number of dimensions through data flattening. We show how VRV increases the power of Radviz through these extra dimensions by enhancing the flexibility in the layout of the DAs. We apply VRV to the problem of analyzing the results of multiple clusterings of the same data set, called multiple cluster sets or cluster ensembles. We show how features of VRV help discern patterns across the multiple cluster sets. We use the Iris data set to explain VRV and a newt gene microarray data set used in studying limb regeneration to show its utility. We then discuss further applications of VRV.