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Psychometrika

, Volume 39, Issue 4, pp 373–421 | Cite as

Representation of structure in similarity data: Problems and prospects

  • Roger N. Shepard
Article

Conclusion

After struggling with the problem of representing structure in similarity data for over 20 years, I find that a number of challenging problems still remain to be overcome—even in the simplest case of the analysis of a single symmetric matrix of similarity estimates. At the same time, I am more optimistic than ever that efforts directed toward surmounting the remaining difficulties will reap both methodological and substantive benefits. The methodological benefits that I forsee include both an improved efficiency and a deeper understanding of “discovery” methods of data analysis. And the substantive benefits should follow, through the greater leverage that such methods will provide for the study of complex empirical phenomena—perhaps particularly those characteristic of the human mind.

Keywords

Data Analysis Public Policy Statistical Theory Deep Understanding Similarity Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Psychometric Society 1974

Authors and Affiliations

  • Roger N. Shepard
    • 1
  1. 1.Stanford UniversityUSA

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