Abstract
We present a general framework of hierarchical methods for point cluster analysis on networks, and then consider individual clustering procedures and their time complexities defined by typical variants of distances between clusters. The distances considered here are the closest-pair distance, the farthest-pair distance, the average distance, the median-pair distance and the radius distance. This paper will offer a menu for users to choose hierarchical clustering algorithms on networks from a time complexity point of view.
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Acknowledgements
This study was partly supported by the Grant-in-Aid for Scientific Research (B) No. 20300098 and (B) No. 20360044 of the Japanese Society for Promotion of Science.
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Sugihara, K., Okabe, A. & Satoh, T. Computational method for the point cluster analysis on networks. Geoinformatica 15, 167–189 (2011). https://doi.org/10.1007/s10707-009-0092-5
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DOI: https://doi.org/10.1007/s10707-009-0092-5