Multidimensional Scaling, Tree-Fitting, and Clustering. Shepard, R. N. Science, 210(4468):390–398, 1980. Publisher: American Association for the Advancement of Science
Paper abstract bibtex American mathematical psychologists have developed computer-based methods for constructing representations of the psychological structure of a set of stimuli on the basis of pairwise measures of similarity or confusability. Applications to perceptual and semantic data illustrate how complementary aspects of the underlying psychological structure are revealed by different types of representations, including multidimensional spatial configurations and nondimensional tree-structures or clusterings.
@article{shepard_multidimensional_1980,
title = {Multidimensional {Scaling}, {Tree}-{Fitting}, and {Clustering}},
volume = {210},
issn = {0036-8075},
url = {https://www.jstor.org/stable/1684708},
abstract = {American mathematical psychologists have developed computer-based methods for constructing representations of the psychological structure of a set of stimuli on the basis of pairwise measures of similarity or confusability. Applications to perceptual and semantic data illustrate how complementary aspects of the underlying psychological structure are revealed by different types of representations, including multidimensional spatial configurations and nondimensional tree-structures or clusterings.},
number = {4468},
urldate = {2024-06-20},
journal = {Science},
author = {Shepard, Roger N.},
year = {1980},
note = {Publisher: American Association for the Advancement of Science},
pages = {390--398},
}
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