Fast ordering of large categorical datasets for better visualization

  • Authors:
  • Alina Beygelzimer;Chang-Shing Perng;Sheng Ma

  • Affiliations:
  • University of Rochester, Rochester, NY;IBM T. J. Watson Research Center, Hawthorne, NY;IBM T. J. Watson Research Center, Hawthorne, NY

  • Venue:
  • Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
  • Year:
  • 2001

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Abstract

An important issue in visualizing categorical data is how to order categorical values. The focus of this paper is on constructing such orderings efficiently without compromising their visual quality.