Refereed full papers (journals, book chapters, international conferences)

1999

@inproceedings{Fle1999,
	vgclass =	{refpap},
	author =	{Arthur Flexer},
	title =	{On the Use of Self-Organizing Maps for Clustering and
	Visualization},
	editor =	{Zytkow, J. and Rauch, J.},
	booktitle =	{Proceedings of the Third European Conference on Principles
	of Data Mining and Knowledge Discovery (PKDD'99)},
	address =	{Prague, Czech Republic},
	number =	{1704},
	series =	{Lecture Notes in Computer Science},
	pages =	{80--88},
	publisher =	{Springer-Verlag},
	month =	{15--18~September},
	year =	{1999},
	url =	{http://www.ai.univie.ac.at/cgi-bin/tr-online?number+99-04},
	url1 =	{http://www.oefai.at/cgi-bin/get-tr?paper=oefai-tr-99-04.pdf},
	url2 =	{http://www.oefai.at/cgi-bin/get-tr?paper=oefai-tr-99-04.ps.gz},
	abstract =	{We will show that the number of output units used in a
	self-organizing map (SOM) influences its applicability for either
	clustering or visualization. By reviewing the appropriate literature
	and theory as well as our own empirical results, we demonstrate that
	SOMs can be used for clustering or visualization separately, for
	simultaneous clustering and visualization, and even for clustering via
	visualization. For all these different kinds of application, SOM is
	compared to other statistical approaches. This will show SOM to be a
	very flexible tool which can be used for various forms of explorative
	data analysis but it will also be made obvious that this flexibility
	comes with a price in terms of impaired performance.},
}