IEEE Conference on Information Visualization : an International Conference on Computer Visualization & Graphics, proceedings ... IEEE Conference on Information Visualization最新文献

Uvf - Unified Volume Format: A General System for Efficient Handling of Large Volumetric Datasets. 统一卷格式:有效处理大体积数据集的通用系统。

IEEE Conference on Information Visualization : an International Conference on Computer Visualization & Graphics, proceedings ... IEEE Conference on Information Visualization Pub Date : 2008-01-01

Jens Krüger, Kristin Potter, Rob S Macleod, Christopher Johnson

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引用次数: 0

Special Issue of selected and extended InfoVis '03 papers - Guest Editor' Introduction 2003年InfoVis论文选编特刊——特邀编辑简介

IEEE Conference on Information Visualization : an International Conference on Computer Visualization & Graphics, proceedings ... IEEE Conference on Information Visualization Pub Date : 2004-01-01 DOI: 10.1057/palgrave.ivs.9500073

S. North, T. Munzner

引用次数: 0

Exploring High-D Spaces with Multiform Matrices and Small Multiples. 用多形式矩阵和小倍数探索高维空间。

IEEE Conference on Information Visualization : an International Conference on Computer Visualization & Graphics, proceedings ... IEEE Conference on Information Visualization Pub Date : 2003-01-01 DOI: 10.1109/INFVIS.2003.1249006

Alan Maceachren, Xiping Dai, Frank Hardisty, Diansheng Guo, Gene Lengerich

{"title":"Exploring High-D Spaces with Multiform Matrices and Small Multiples.","authors":"Alan Maceachren, Xiping Dai, Frank Hardisty, Diansheng Guo, Gene Lengerich","doi":"10.1109/INFVIS.2003.1249006","DOIUrl":"https://doi.org/10.1109/INFVIS.2003.1249006","url":null,"abstract":"We introduce an approach to visual analysis of multivariate data that integrates several methods from information visualization, exploratory data analysis (EDA), and geovisualization. The approach leverages the component-based architecture implemented in GeoVISTA Studio to construct a flexible, multiview, tightly (but generically) coordinated, EDA toolkit. This toolkit builds upon traditional ideas behind both small multiples and scatterplot matrices in three fundamental ways. First, we develop a general, MultiForm, Bivariate Matrix and a complementary MultiForm, Bivariate Small Multiple plot in which different bivariate representation forms can be used in combination. We demonstrate the flexibility of this approach with matrices and small multiples that depict multivariate data through combinations of: scatterplots, bivariate maps, and space-filling displays. Second, we apply a measure of conditional entropy to (a) identify variables from a high-dimensional data set that are likely to display interesting relationships and (b) generate a default order of these variables in the matrix or small multiple display. Third, we add conditioning, a kind of dynamic query/filtering in which supplementary (undisplayed) variables are used to constrain the view onto variables that are displayed. Conditioning allows the effects of one or more well understood variables to be removed from the analysis, making relationships among remaining variables easier to explore. We illustrate the individual and combined functionality enabled by this approach through application to analysis of cancer diagnosis and mortality data and their associated covariates and risk factors.","PeriodicalId":88889,"journal":{"name":"IEEE Conference on Information Visualization : an International Conference on Computer Visualization & Graphics, proceedings ... IEEE Conference on Information Visualization","volume":" ","pages":"31-38"},"PeriodicalIF":0.0,"publicationDate":"2003-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/INFVIS.2003.1249006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30165186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 110

Beamtrees: compact visualization of large hierarchies 梁树:大型层次结构的紧凑可视化

IEEE Conference on Information Visualization : an International Conference on Computer Visualization & Graphics, proceedings ... IEEE Conference on Information Visualization Pub Date : 2002-10-28 DOI: 10.1057/palgrave.ivs.9500036

F. V. Ham, J. V. Wijk

引用次数: 107

Pixel bar charts: a visualization technique for very large multi-attribute data sets? 像素条形图:非常大的多属性数据集的可视化技术?

IEEE Conference on Information Visualization : an International Conference on Computer Visualization & Graphics, proceedings ... IEEE Conference on Information Visualization Pub Date : 2002-03-01 DOI: 10.1057/palgrave/ivs/9500003

D. Keim, M. Hao, U. Dayal, M. Hsu

引用次数: 114

Presentation, Visualization, What's Next? 演示，可视化，下一步是什么?

IEEE Conference on Information Visualization : an International Conference on Computer Visualization & Graphics, proceedings ... IEEE Conference on Information Visualization Pub Date : 2000-10-09 DOI: 10.1109/INFOVIS.2000.10000

J. Mackinlay

引用次数: 1

Keynote Address: Information Visualization: Wings for the Mind 主题演讲:信息可视化:心灵之翼

IEEE Conference on Information Visualization : an International Conference on Computer Visualization & Graphics, proceedings ... IEEE Conference on Information Visualization Pub Date : 1995-10-30 DOI: 10.1109/INFOVIS.1995.10002

S. Card

引用次数: 1

Case study: Narcissus: visualising information 案例研究:水仙:可视化信息

IEEE Conference on Information Visualization : an International Conference on Computer Visualization & Graphics, proceedings ... IEEE Conference on Information Visualization Pub Date : 1995-01-01 DOI: 10.1109/INFVIS.1995.528691

R. Hendley, N. Drew, Andrew Wood, R. Beale

引用次数: 74