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Datasets which are identical over a number of statistical properties, yet produce dissimilar graphs, are frequently used to illustrate the importance of graphical representations when exploring data. This paper presents a novel method for generating such datasets, along with several examples. Our technique varies from previous approaches in that new datasets are iteratively generated from a seed dataset through random perturbations of individual data points, and can be directed towards a desired outcome through a simulated annealing optimization strategy.
I. Cadez, D. Heckerman, C. Meek, P. Smyth, and S. White. Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, page 280--284. New York, NY, USA, ACM, (2000)
F. Hermans, M. Pinzger, and A. van Deursen. (2011)cite arxiv:1111.6895Comment: 9 Pages, 5 Colour Figures; Proc. European Spreadsheet Risks Int. Grp. (EuSpRIG) 2011 ISBN 978-0-9566256-9-4.