An introduction to splines for use in computer graphics & geometric modeling
An introduction to splines for use in computer graphics & geometric modeling
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Hierarchical parallel coordinates for exploration of large datasets
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Designing Pixel-Oriented Visualization Techniques: Theory and Applications
IEEE Transactions on Visualization and Computer Graphics
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Direct manipulation of parallel coordinates
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Similarity Clustering of Dimensions for an Enhanced Visualization of Multidimensional Data
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Uncovering Clusters in Crowded Parallel Coordinates Visualizations
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INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
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IEEE Transactions on Visualization and Computer Graphics
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IEEE Transactions on Visualization and Computer Graphics
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Scattering Points in Parallel Coordinates
IEEE Transactions on Visualization and Computer Graphics
Topic and keyword re-ranking for LDA-based topic modeling
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Visual clustering in parallel coordinates
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Splatting the lines in parallel coordinates
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
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The high-dimensional nature of the textual data complicates the design of visualization tools to support exploration of large document corpora. In this article, we first argue that the Parallel Coordinates (PC) technique, which can map multidimensional vectors onto a 2D space in such a way that elements with similar values are represented as similar poly-lines or curves in the visualization space, can be used to help users discern patterns in document collections. The inherent reduction in dimensionality during the mapping from multidimensional points to 2D lines, however, may result in visual complications. For instance, the lines that correspond to clusters of objects that are separate in the multidimensional space may overlap each other in the 2D space; the resulting increase in the number of crossings would make it hard to distinguish the individual document clusters. Such crossings of lines and overly dense regions are significant sources of visual clutter, thus avoiding them may help interpret the visualization. In this article, we note that visual clutter can be significantly reduced by adjusting the resolution of the individual term coordinates by clustering the corresponding values. Such reductions in the resolution of the individual term-coordinates, however, will lead to a certain degree of information loss and thus the appropriate resolution for the term-coordinates has to be selected carefully. Thus, in this article we propose a controlled clutter reduction approach, called Parallel hierarchical Coordinates (or PhC), for reducing the visual clutter in PC-based visualizations of text corpora. We define visual clutter and information loss measures and provide extensive evaluations that show that the proposed PhC provides significant visual gains (i.e., multiple orders of reductions in visual clutter) with small information loss during visualization and exploration of document collections.