Result: CLUSCALE (CLUstering and multidimensional SCAL[E]ing) : A three-way hybrid model incorporating overlapping clustering and multidimensional scaling structure

Title:
CLUSCALE (CLUstering and multidimensional SCAL[E]ing) : A three-way hybrid model incorporating overlapping clustering and multidimensional scaling structure
Authors:
CHATURVEDI, Anil, CANOIL, J. Douglas
Source:
Journal of classification. 23(2):269-299
Publisher Information:
New York, NY: Springer, 2006.
Publication Year:
2006
Physical Description:
print, 1 p.3/4
Original Material:
INIST-CNRS
Subject Terms:
Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Probabilités et statistiques, Probability and statistics, Statistiques, Statistics, Analyse multivariable, Multivariate analysis, Sciences appliquees, Applied sciences, Recherche operationnelle. Gestion, Operational research. Management science, Recherche opérationnelle et modèles formalisés de gestion, Operational research and scientific management, Optimisation. Problèmes de recherche, Optimization. Search problems, Programmation mathématique, Mathematical programming, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Analyse corrélation, Correlation analysis, Análisis correlación, Analyse covariance, Covariance analysis, Análisis covariancia, Analyse donnée, Data analysis, Análisis datos, Analyse multivariable, Multivariate analysis, Análisis multivariable, Analyse variance 3 critères, Three way analysis of variance, Análisis variancia 3 criterios, Chevauchement, Overlap, Imbricación, Classification automatique (statistiques), Cluster analysis (statistics), Echelonnement multidimensionnel, Multidimensional scaling, Escala multidimensional, Hétérogénéité, Heterogeneity, Heterogeneidad, Modèle hybride, Hybrid model, Modelo híbrido, Métrique, Metric, Métrico, Programmation en nombres entiers, Integer programming, Programación entera, CLUSCALE, Clustering, INDCLUS, INDSCAL, Modèle discret paramètre, Discrete parameter modeling, Optimisation non linéaire, Analysis of correlation data, Analysis of covariance data, Cluster analysis, MDS, Metric analysis, Mixed integer programming,, Multi-linear model, Nonlinear optimization, Overlapping clusters, Perceptual mapping' 3-way' Three-way analysis, Tri-linear model, Variance decomposition
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Capital One, McLean, Virginia, United States
Rutgers University, Newark NJ, United States
ISSN:
0176-4268
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=18312446
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems

Mathematics

Operational research. Management
Accession Number:
edscal.18312446
Database:
PASCAL Archive

Further Information

Traditional techniques of perceptual mapping hypothesize that stimuli are differentiated in a common perceptual space of quantitative attributes. This paper enhances traditional perceptual mapping techniques such as multidimensional scaling (MDS) which assume only continuously valued dimensions by presenting a model and methodology called CLUSCALE for capturing stimulus differentiation due to perceptions that are qualitative, in addition to quantitative or continuously varying perceptual attributes or dimensions. It provides models and OLS parameter estimation procedures for both a two-way and a three-way version of this general model. Since the two-way version of the model and method has already been discussed by Chaturvedi and Carroll (2000), and a stochastic variant discussed by Navarro and Lee (2003), we shall deal in this paper almost entirely with the three-way version of this model. We recommend the use of the three-way approach over the two-way approach, since the three-way approach both accounts for and takes advantage of the heterogeneity in subjects' perceptions of stimuli to provide maximal information; i.e., it explicitly deals with individual differences among subjects.