Title :
VAST to Knowledge: Combining tools for exploration and mining
Author :
Auvil, Loretta ; Llorà, Xavier ; Searsmith, Duane ; Searsmith, Kelly
Author_Institution :
Univ. of Illinois at Urbana-Champaign, Urbana
fDate :
Oct. 30 2007-Nov. 1 2007
Abstract :
The investigation of the VAST Contest collection provided a valuable test for text mining techniques. Our group has focused on creating analytical tools to unveil relevant patterns and to aid with the content navigation in such text collections. Our results show how such an approach, in combination with visualization techniques, can ease the discovery process especially when multiple tools founded on the same approach to data mining are used in complement to and in concert with one another.
Keywords :
data mining; data visualisation; text analysis; VAST; data mining; data visualization; knowledge discovery; knowledge exploration; text mining; visual analytics; Artificial intelligence; Automatic testing; Data mining; Data visualization; Electronic mail; Information analysis; Natural language processing; Navigation; Pattern analysis; Text mining; Text mining; digital libraries; information visualization; knowledge discovery; visual analytics;
Conference_Titel :
Visual Analytics Science and Technology, 2007. VAST 2007. IEEE Symposium on
Conference_Location :
Sacramento, CA
Print_ISBN :
978-1-4244-1659-2
DOI :
10.1109/VAST.2007.4389015
