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Data clustering and analyzing techniques using hierarchical clustering method

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Abstract

Data clustering and analyzing techniques are studied by using hierarchical clustering method. A matrix of words is constructed with a randomly chosen RSS list. By collecting data from this list a matrix is built. In the matrix each row corresponds to a article and each column represents a word. Based on the matrix a hierarchical clustering algorithm is designed. In this algorithm the Pearson correlation coefficient is used to compute the distances among different contents. The dendrogram is used to describe the hierarchical relationship of contents and words. And the 2-D graph also is used to represent the dendrogram in another format.

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Acknowledgments

This research is supported by Natural Science Foundation of Heilongjiang Province (F201034); Scientific Research Foundation for Doctor of Harbin University of Commerce (12DL024)

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Authors and Affiliations

  1. School of Computer and Information Engineering, Harbin University of Commerce, 150028, Harbin, China

    Wen Hu & Qing he Pan

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  1. Wen Hu
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  2. Qing he Pan
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Correspondence to Qing he Pan.

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Hu, W., he Pan, Q. Data clustering and analyzing techniques using hierarchical clustering method. Multimed Tools Appl 74, 8495–8504 (2015). https://doi.org/10.1007/s11042-013-1611-9

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  • DOI: https://doi.org/10.1007/s11042-013-1611-9

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