Title :
Icon-based visualization of large high-dimensional datasets
Author :
Chen, Ping ; Hu, Chenyi ; Ding, Wei ; Lynn, Heloise ; Simon, Yves
Author_Institution :
Dept. of Comput. & Math. Sci., Univ. of Houston, TX, USA
Abstract :
High dimensional data visualization is critical to data analysts since it gives a direct view of original data. We present a method to visualize large amount of high dimensional data. We divide dimensions of data into several groups. Then, we use one icon to represent each group, and associate visual properties of each icon with dimensions in each group. A high dimensional data record will be represented by multiple different types of icons located in the same position. Furthermore, we use summary icons to display local details of viewer´s interests and the whole data set at meantime. We show its effectiveness and efficiency through a case study on a real large data set.
Keywords :
data visualisation; graphical user interfaces; knowledge acquisition; rendering (computer graphics); very large databases; data analysts; high dimensional data record; high dimensional data visualization; icon visual properties; icon-based visualization; summary icons; Data analysis; Data mining; Data visualization; Displays; Histograms; Humans; Pattern recognition; Rendering (computer graphics); Scattering; Shape control;
Conference_Titel :
Data Mining, 2003. ICDM 2003. Third IEEE International Conference on
Print_ISBN :
0-7695-1978-4
DOI :
10.1109/ICDM.2003.1250963