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

Denny, Graham J. Williams, Peter Christen

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

11 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 - 1 Dec 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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