Abstract
Results from empirical studies on automatic visualization systems for statistical data are reported. These studies especially focused on a mechanism for choosing an appropriate graph type. Two experiments were conducted as a first step fowards proposing a mechanism with objective bases.
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© 2000 Springer-Verlag Berlin Heidelberg
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Yonezawa, H., Matsushita, M., Kato, T. (2000). Criteria to Choose Appropriate Graph-Types. In: Mizoguchi, R., Slaney, J. (eds) PRICAI 2000 Topics in Artificial Intelligence. PRICAI 2000. Lecture Notes in Computer Science(), vol 1886. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44533-1_112
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DOI: https://doi.org/10.1007/3-540-44533-1_112
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67925-7
Online ISBN: 978-3-540-44533-3
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