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- W2019969045 abstract "The real world data distribution is seldom uniform. Clutter and sparsity commonly occur in visualization. Often, clutter results in overplotting, in which certain data items are not visible because other data items occlude them. Sparsity results in the inefficient use of the available display space. Common mechanisms to overcome this include reducing the amount of information displayed or using multiple representations with a varying amount of detail. This paper describes out experiments on Non-Linear Visual Space Transformations (NLVST). NLVST encompasses several innovative techniques: (1) employing a histogram for calculating the density of data distribution; (2) mapping the raw data values to a non-linear scale for stretching a high-density area; (3) tightening the sparse area to save the display space; (4) employing different color ranges of values on a non-linear scale according to the local density. We have applied NLVST to several web applications: market basket analysis, transactions observation, and IT search behavior analysis.© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only." @default.
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- W2019969045 date "2002-03-11" @default.
- W2019969045 modified "2023-09-22" @default.
- W2019969045 title "<title>Visualization of high-density 3D graphs using nonlinear visual space transformations</title>" @default.
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- W2019969045 doi "https://doi.org/10.1117/12.458795" @default.
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