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Feinman, R. D.; Kwok, K. L. – Journal of the American Society for Information Science, 1973
A study was undertaken to classify mechanically a document collection using the free-language words in titles and abstracts of physics research papers. Using a clustering algorithm, results were obtained which closely duplicated clusters obtained by previous experiments with citations. A brief comparison is made with a traditional manual…
Descriptors: Algorithms, Classification, Cluster Analysis, Databases
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Waller, Niels G.; Kaiser, Heather A.; Illian, Janine B.; Manry, Mike – Psychometrika, 1998
The classification capabilities of the one-dimensional Kohonen neural network (T. Kohonen, 1995) were compared with those of two partitioning and three hierarchical cluster methods in 2,580 data sets with known cluster structure. Overall, the performance of the Kohonen networks was similar to, or better than, that of the others. Implications for…
Descriptors: Algorithms, Classification, Cluster Analysis, Comparative Analysis
Peer reviewed Peer reviewed
Yu, Clement T. – Journal of the American Society for Information Science, 1974
A clustering algorithm which is tree-like in structure, and is based on user queries, is presented. It is compared to some existing algorithms and is found to be superior. (Author)
Descriptors: Algorithms, Classification, Cluster Analysis, Cluster Grouping
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Price, Lydia J. – Multivariate Behavioral Research, 1993
The ability of the NORMIX algorithm to recover overlapping population structures was compared to the OVERCLUS procedure and another clustering procedure in a Monte Carlo study. NORMIX is found to be more accurate than other procedures in recovering overlapping population structure when appropriate implementation options are specified. (SLD)
Descriptors: Algorithms, Classification, Cluster Analysis, Comparative Analysis
Peer reviewed Peer reviewed
Schweizer, Karl – Multivariate Behavioral Research, 1991
A mathematical formula is introduced for the effect of integrating data. A method is then derived to eliminate the effect from correlations of variables, including mean composites, thus allowing for a clustering algorithm that requires allocation of variables according to the magnitude of their correlations. Examples illustrate the procedure. (SLD)
Descriptors: Algorithms, Classification, Cluster Analysis, Computer Simulation
Peer reviewed Peer reviewed
Griffiths, Alan; And Others – Journal of Documentation, 1984
Considers classifications produced by application of single linkage, complete linkage, group average, and word clustering methods to Keen and Cranfield document test collections, and studies structure of hierarchies produced, extent to which methods distort input similarity matrices during classification generation, and retrieval effectiveness…
Descriptors: Algorithms, Classification, Cluster Analysis, Cluster Grouping