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Principles of Multivariate Data Visualization

  • Huh, Moon Yul (Department of Statistics, SungKyunKwan University) ;
  • Cha, Woon Ock (Division of Computer Engineering, Hansung University)
  • 발행 : 2004.12.01

초록

Data visualization is the automation process and the discovery process to data sets in an effort to discover underlying information from the data. It provides rich visual depictions of the data. It has distinct advantages over traditional data analysis techniques such as exploring the structure of large scale data set both in the sense of number of observations and the number of variables by allowing great interaction with the data and end-user. We discuss the principles of data visualization and evaluate the characteristics of various tools of visualization according to these principles.

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참고문헌

  1. Blake, C .L. & Merz, C. J (1998). UCI Repository of machine learning databases, Department of Information and Computer Science, University of California, Irvine, CA (http://www.ics.uci.edurmlearn/MLRepository.htmI)
  2. Catarci, T., $\'{D}$Amore, F., Janecek, P., Spaccapietra, S., Interacting with GIS: from paper cartography to virtual environments Unesco Encyclopedia on man-machine Interfaces, Advanced Geographic Information Systems, Unesco Press (in Press). available as a pdf file at http://hcLepfl.ch/website/publications/200l/EOLSS -with_images.pdf
  3. Cleveland, W. S. and McGill, R. (1985). Graphical Perception and Graphical Methods for Analyzing Scientific Data. Science, 229, 828-833 https://doi.org/10.1126/science.229.4716.828
  4. Cleveland, W. S. (1993). Visualizing Data. AT&T Bell Lab, Murray Hill
  5. Dawson, R. J. (1995). http://ssi.umh.ac.be/titanic.html
  6. Friendly, Michael (1994). Mosaic Displays for Multi-Way Contingency Tables, Journal of the American Statistical Association, 89, 190-200 https://doi.org/10.2307/2291215
  7. Friendly, Michael (1999). Extending Mosaic Displays: Marginal, Partial, and Conditional Views of Categorical Data, Journal of Computational and Graphical Statistics, 8, 373-395 https://doi.org/10.2307/1390863
  8. Grinstein, G. G. and Ward, M. (2002). Introduction to data Visualization in Iriformation Visualization in Data Mining and Knowledge Discovery edited by Fayyad, u., Grinstein, G. G. and Wierse, A., Morgan Kaufmann publishers
  9. Huh, M. Y. and Song, K. R. (2002). DAVIS: A Java-based data visualization system, Computational Statistics, 17(3), 411-423 https://doi.org/10.1007/s001800200116
  10. Huh, M. Y. (2004). Line Mosaic Plot: Algorithm and Implementation, invited paper, COMPSTAT 4, Prague, Chech
  11. McLeod, A. I. & Provost, S. B. (2001). Multivariate Data Visualization, Encyclopedia of Environmetrics, 1333-1344, Edited by Abdel El-shaarawi and Walter Piegorsch, New York, Wiley
  12. Nicholas, C. J. (1999). The Emergence of Data Visualization and Prospects for its Business Applications, Masters of Information systems Management Professional Seminar
  13. Steven, S. S. (1975). Psychophysics : Introduction to its Perceptual, Neural, and Social Prospects. New York: Wiley