Title :
HD-Eye: visual mining of high-dimensional data
Author :
Hinneburg, Alexander ; Keim, Daniel A. ; Wawryniuk, Markus
Author_Institution :
Inst. of Comput. Sci., Halle Univ., Germany
Abstract :
Clustering in high-dimensional databases poses an important problem. However, we can apply a number of different clustering algorithms to high-dimensional data. The authors consider how an advanced clustering algorithm combined with new visualization methods interactively clusters data more effectively. Experiments show these techniques improve the data mining process
Keywords :
data mining; data visualisation; very large databases; HD-Eye; data clustering; data visualization; high-dimensional databases; very large databases; visual data mining; Clustering algorithms; Data mining; Data visualization; Density functional theory; Displays; Kernel; Multidimensional systems; Particle separators; Principal component analysis; Statistical analysis;
Journal_Title :
Computer Graphics and Applications, IEEE
