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Ordinal preference and inter-rater pattern recognition: Hopfield neural network vs. measures of association

Ordinal preference and inter-rater pattern recognition: Hopfield neural network vs. measures of... In decision analysis, if the criterion is an ordinal rather than a cardinal one, a preferential solution depends on the inter-rater agreement. The Kendall coefficient of concordance W, the Friedman ranks statistic F r , and the Page L statistic are often used to determine the association among M sets of rankings. However, they may get some anomalies because they all use the cardinal variable “variance” to judge the association. In order to correct the anomalies, we use the modified Hopfield neural network instead to determine the association among M sets of rankings. The results are not only to reduce the unidentified cases but also to solve the anomalies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence Review Springer Journals

Ordinal preference and inter-rater pattern recognition: Hopfield neural network vs. measures of association

Artificial Intelligence Review , Volume 30 (4) – Oct 27, 2009

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References (26)

Publisher
Springer Journals
Copyright
Copyright © 2009 by Springer Science+Business Media B.V.
Subject
Computer Science; Computer Science, general; Artificial Intelligence (incl. Robotics)
ISSN
0269-2821
eISSN
1573-7462
DOI
10.1007/s10462-009-9118-5
Publisher site
See Article on Publisher Site

Abstract

In decision analysis, if the criterion is an ordinal rather than a cardinal one, a preferential solution depends on the inter-rater agreement. The Kendall coefficient of concordance W, the Friedman ranks statistic F r , and the Page L statistic are often used to determine the association among M sets of rankings. However, they may get some anomalies because they all use the cardinal variable “variance” to judge the association. In order to correct the anomalies, we use the modified Hopfield neural network instead to determine the association among M sets of rankings. The results are not only to reduce the unidentified cases but also to solve the anomalies.

Journal

Artificial Intelligence ReviewSpringer Journals

Published: Oct 27, 2009

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