Title :
Uncovering Clusters in Crowded Parallel Coordinates Visualizations
Author :
Artero, Almir Olivette ; de Oliveira, Maria Cristina F. ; Levkowitz, Haim
Author_Institution :
Dept. of Comput. Sci., Sao Paulo Univ.
Abstract :
The one-to-one strategy of mapping each single data item into a graphical marker adopted in many visualization techniques has limited usefulness when the number of records and/or the dimensionality of the data set are very high. In this situation, the strong overlapping of graphical markers severely hampers the user´s ability to identify patterns in the data from its visual representation. We tackle this problem here with a strategy that computes frequency or density information from the data set, and uses such information in parallel coordinates visualizations to filter out the information to be presented to the user, thus reducing visual clutter and allowing the analyst to observe relevant patterns in the data. The algorithms to construct such visualizations, and the interaction mechanisms supported, inspired by traditional image processing techniques such as grayscale manipulation and thresholding are also presented. We also illustrate how such algorithms can assist users to effectively identify clusters in very noisy large data sets
Keywords :
data mining; data visualisation; image processing; information filters; interactive systems; pattern clustering; user interfaces; very large databases; density-based visualization; graphical marker; grayscale manipulation; image processing techniques; information filter; information visualization; interaction mechanisms; parallel coordinates visualization; pattern identification; visual clustering; visual data mining; Clustering algorithms; Concurrent computing; Data visualization; Frequency; Gray-scale; Image processing; Information analysis; Information filtering; Information filters; Pattern analysis; density-based visualization; information visualization; visual clustering; visual data mining;
Conference_Titel :
Information Visualization, 2004. INFOVIS 2004. IEEE Symposium on
Conference_Location :
Austin, TX
Print_ISBN :
0-7803-8779-3
DOI :
10.1109/INFVIS.2004.68