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Murtagh, F. – Information Processing and Management, 1984
Using examples of data from the areas of information retrieval and of multivariate data analysis, six hierarchic clustering algorithms (single link, median, centroid, group average, complete link, Wards's) are examined and evaluated by using three proposed coefficients of hierarchic structure. Nine references are cited. (EJS)
Descriptors: Algorithms, Cluster Analysis, Cluster Grouping, Data Analysis
Crandall, R. E. – 1973
In this study assumptions are made concerning the amount of clustering in sequences containing runs of equivalent elements. It is assumed that any valid clustering measure is linear with respect to union of runs and monotone increasing under iterations of clustering operators. With these two assumptions it follows that any such measure is of…
Descriptors: Cluster Analysis, Cluster Grouping, Data Analysis, Measurement Techniques
Hubert, Lawrence; Schultz, James – 1975
An empirical assesssment of the space distortion properties of two prototypic hierarchical clustering procedures is given in terms of an occupancy model developed from combinatorics. Using one simple example, the single-link and complete-link clustering strategies now in common use in the behavioral sciences are empirically shown to be space…
Descriptors: Behavioral Sciences, Classification, Cluster Analysis, Cluster Grouping
Peer reviewed Peer reviewed
McQuitty, Louis L.; Koch, Valerie L. – Educational and Psychological Measurement, 1976
A relatively reliable and valid hierarchy of clusters of objects is plotted from the highest column entries, exclusively, of a matrix of interassociations between the objects. Having developed out of a loose definition of types, the method isolates both loose and highly definitive types, and all those in between. (Author/RC)
Descriptors: Cluster Analysis, Cluster Grouping, Comparative Analysis, Data Analysis
Shafto, Michael – 1972
The purpose of this paper is to suggest a technique of cluster analysis which is similar in aim to the Interactive Intercolumnar Correlation Analysis (IICA), though different in detail. Two methods are proposed for extracting a single bipolar factor (a "contrast compenent") directly from the initial similarities matrix. The advantages of this…
Descriptors: Bibliographies, Classification, Cluster Analysis, Cluster Grouping
Peer reviewed Peer reviewed
Yerkey, A. Neil – Journal of the American Society for Information Science, 1983
This study attempts to analyze descriptors taken from subject categories in ERIC thesaurus and used as search terms on CROSS database Bibliographic Retrieval Services. An expectation ratio was computed and cluster analysis was conducted to discover subject relationships among databases. A list of databases retrieved and 12 references are appended.…
Descriptors: Cluster Analysis, Cluster Grouping, Comparative Analysis, Data Analysis
Gray, William M.; Hofmann, Richard J. – 1969
Most responses to educational and psychological test items may be represented in binary form. However, such dichotomously scored items present special problems when an analysis of correlational interrelationships among the items is attempted. Two general methods of analyzing binary data are proposed by Horst to partial out the effects of…
Descriptors: Algorithms, Analysis of Covariance, Cluster Analysis, Cluster Grouping
Stein, Joan Lerner; And Others – 1975
Research on 128 children is presented as evidence of the superiority of a new clustering measure (X) over a more traditional "chance clustering" measure (sigma) as a means of organizing material to be learned to facilitate recall. X is shown to meet three criteria for a measure of a developmental process: X is more highly correlated with recall…
Descriptors: Age Differences, Cluster Analysis, Cluster Grouping, Cognitive Development
Pinto, Patrick R.; Pinder, Craig C. – 1972
Two hundred twenty-seven organizational units drawn from a variety of industries were cluster-analyzed on the basis of their similarities across 18 behavioral and structural dimensions of effectiveness. Using a multivariate subgrouping procedure, eight homogeneous clusters of units were found, varying in size from 8-65 units, and each…
Descriptors: Behavior Rating Scales, Behavioral Science Research, Classification, Cluster Analysis