ReDSOM: Relative density visualization of temporal changes in cluster structures using self-organizing maps

Denny*, Graham J. Williams, Peter Christen

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    12 Citations (Scopus)

    Abstract

    We introduce a Self-Organizing Map (SOM) based visualization method that compares cluster structures in temporal datasets using Relative Density SOM (ReDSOM) visualization. Our method, combined with a distance matrix-based visualization, is capable of visually identifying emerging clusters, disappearing clusters, enlarging clusters, contracting clusters, the shifting of cluster centroids, and changes in cluster density. For example, when a region in a SOM becomes significantly more dense compared to an earlier SOM, and well separated from other regions, then the new region can be said to represent a new cluster. The capabilities of ReDSOM are demonstrated using synthetic datasets, as well as real-life datasets from the World Bank and the Australian Taxation Office. The results on the real-life datasets demonstrate that changes identified interactively can be related to actual changes. The identification of such cluster changes is important in many contexts, including the exploration of changes in population behavior in the context of compliance and fraud in taxation.

    Original languageEnglish
    Title of host publicationProceedings - 8th IEEE International Conference on Data Mining, ICDM 2008
    Pages173-182
    Number of pages10
    DOIs
    Publication statusPublished - 2008
    Event8th IEEE International Conference on Data Mining, ICDM 2008 - Pisa, Italy
    Duration: 15 Dec 200819 Dec 2008

    Publication series

    NameProceedings - IEEE International Conference on Data Mining, ICDM
    ISSN (Print)1550-4786

    Conference

    Conference8th IEEE International Conference on Data Mining, ICDM 2008
    Country/TerritoryItaly
    CityPisa
    Period15/12/0819/12/08

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