Abstract
For the analysis of communities in social networks several data mining techniques have been developed such as the DenGraph algorithm to study the dynamics of groups in graph structures. The here proposed DenGraph-HO algorithm is an extension of the density-based graph clusterer DenGraph. It produces a cluster hierarchy that can be used to implement a zooming operation for visual social network analysis. The clusterings in the hierarchy fulfill the DenGraph-O paradigms and can be efficiently computed. We apply DenGraph-HO on a data set obtained from the music platform Last.fm and demonstrate its usability. © Springer-Verlag London Limited 2011.
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CITATION STYLE
Schlitter, N., Falkowski, T., & Lâ̈assig, J. (2011). DenGraph-HO: Density-based hierarchical community detection for explorative visual network analysis. In Res. and Dev. in Intelligent Syst. XXVIII: Incorporating Applications and Innovations in Intel. Sys. XIX - AI 2011, 31st SGAI Int. Conf. on Innovative Techniques and Applications of Artificial Intel. (pp. 283–296). Springer London. https://doi.org/10.1007/978-1-4471-2318-7_22
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