Talks and Poster Presentations (with Proceedings-Entry):
G. Pölzlbauer, A. Rauber, M. Dittenbach:
"A Vector Field Visualization Technique for Self-organizing Maps";
Talk: 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2005,
- 2005-05-20; in: "Advances in Knowledge Discovery and Data Mining",
Lecture Notes in Artificial Intelligence 3518
The Self-Organizing Map is one of most prominent tools for the analysis
and visualization of high-dimensional data.
We propose a novel visualization technique for
Self-Organizing Maps which can be displayed either as a vector
field where arrows point to cluster centers, or as
a plot that stresses cluster borders. A parameter is
provided that allows for visualization of the cluster structure at different levels of detail.
Furthermore, we present a number of experimental results using
standard data mining benchmark data.
Online library catalogue of the TU Vienna:
Project Head A Min Tjoa:
Created from the Publication Database of the Vienna University of Technology.