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program. For each sample five spectra were collected. Chemometrics Similarities between FT-Raman spectra were studied using Hierarchical Cluster Analysis (program Opus/Bruker package 5.1). The spectra were not baseline

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, scholars usually cluster analysis, multidimensional scaling analysis and factor analysis to conduct co-citation analysis. Compared to the scholars’ traditional qualitative analysis (including individual induction, interviews and other subjective methods

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, P. J. ( 1990 ): Finding Groups in Data: An Introduction to Cluster Analysis . New York: John&Wiley . Kruskal , J. B. ( 1964 ): Nonmetric Multidimensional Scaling: A

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problems in a method of cluster analysis. Biometrics 27 :501-514. Practical problems in a method of cluster analysis Biometrics 501 514

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statistical significant difference between the two classes of diseases in the proportions of missing papers. For each year, a Kruskal–Wallis rank sum test yielded a non-significant result [χ 2 (1) < 1.5, P > 0.05]. Cluster analysis

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Cluster Analysis , John Wiley & Sons, New York, 1999 . [29] H.C. Romesburg , Cluster Analysis for Researchers, Lifetime Learning

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Souza, E., Sorrells, M.E. 1991. Relationships among 70 American oat germplasms. I. Cluster analysis using quantitative characters. Crop Sci. 31 :599–605. Sorrells M.E. Relationships

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conduct a literature review. Then we introduce the data set and the method HDCCA with its realization steps. In the next part, we construct the hybrid documents co-citation network, and apply both cluster analysis and network analysis to uncover the

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1993 106 13 20 Ng, A., Jordan, M. and Weiss, Y. 2001. On spectral clustering: analysis and an algorithm. Advances in

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Fig. 4 Dendrogram of the authors in 11-Slice Twelve groups are forming according to the cluster analysis from bottom to top. Group 1, group 3, group 4, group7, group 8 all come from

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