Visualization of Cluster Changes by Comparing Self-organizing Maps

  title={Visualization of Cluster Changes by Comparing Self-organizing Maps},
  author={Denny and David McG. Squire},
In this paper we introduce Self-Organizing Map-based techniques that can reveal structural cluster changes in two related data sets from different time periods in a way that can explain the new result in relation to the previous one. These techniques are demonstrated using a real-world data set from the World Development Indicators database maintained by the World Bank. The results verify that the methods are capable of revealing changes in cluster strucure and membership, corresponding to… CONTINUE READING
Highly Cited
This paper has 18 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 10 extracted citations

Relative density estimation using Self-Organizing Maps

2014 International Conference on Advanced Computer Science and Information System • 2014
View 1 Excerpt

A Self-Organizing Time Map for time-to-event data

2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM) • 2013
View 1 Excerpt


Publications referenced by this paper.
Showing 1-10 of 16 references

Self-Organizing Maps

View 3 Excerpts
Highly Influenced

Structures of welfare and poverty in the world discovered by the Self-Organizing Map

S. Kaski, T. Kohonen
Report A24, Helsinki University of Technology, Faculty of Information Technology, Laboratory of Computer and Information Science, Espoo, Finland • 1995
View 3 Excerpts
Highly Influenced

Visualizations of cluster changes by comparing self-organizing maps

Master’s minor thesis, School of Computer Science and Software Engineering, Monash University, 900 Dandenong Road Caulfield, Victoria 3145, Australia • 2004
View 2 Excerpts

Clustering of the self-organizing map

IEEE Trans. Neural Netw. Learning Syst. • 2000
View 1 Excerpt

Similar Papers

Loading similar papers…