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On the classification of recall strings using lattice-theoretic measures

On the classification of recall strings using lattice-theoretic measures Lattice theory is used to develop techniques for classifying groups of subjects on the basis of their recall strategies or multiple recall strategies within individual subjects. Using the ordered tree algorithm to represent sets of recall orders, it is shown how both trees and single recall strings can be represented as points within a nonsemimodular, graded lattice. Distances within the lattice structure are used to construct a dissimilarity measure,S, which can then be used to partition the individual recall strings. The measureS between strings is compared to Kendall's tau in three empirical tests, examining differences between individual subjects, differences between groups of subjects, and differences within a subject. It was shown that onlyS could recover the original differences. Differences between comparing chunks versus comparing orders are discussed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Classification Springer Journals

On the classification of recall strings using lattice-theoretic measures

Hirtle, Stephen
Journal of Classification , Volume 4 (2) – Jun 18, 2005
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References (17)

Publisher
Springer Journals
Copyright
Copyright © 1987 by Springer-Verlag
Subject
Statistics; Statistical Theory and Methods; Pattern Recognition; Bioinformatics; Signal,Image and Speech Processing; Psychometrics; Marketing
ISSN
0176-4268
eISSN
1432-1343
DOI
10.1007/BF01896988
Publisher site
See Article on Publisher Site

Abstract

Lattice theory is used to develop techniques for classifying groups of subjects on the basis of their recall strategies or multiple recall strategies within individual subjects. Using the ordered tree algorithm to represent sets of recall orders, it is shown how both trees and single recall strings can be represented as points within a nonsemimodular, graded lattice. Distances within the lattice structure are used to construct a dissimilarity measure,S, which can then be used to partition the individual recall strings. The measureS between strings is compared to Kendall's tau in three empirical tests, examining differences between individual subjects, differences between groups of subjects, and differences within a subject. It was shown that onlyS could recover the original differences. Differences between comparing chunks versus comparing orders are discussed.

Journal

Journal of Classification – Springer Journals

Published: Jun 18, 2005

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