DocumentCode
2218862
Title
VAST to Knowledge: Combining tools for exploration and mining
Author
Auvil, Loretta ; Llorá, Xavier ; Searsmith, Duane ; Searsmith, Kelly
Author_Institution
Automated Learning Group, National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign. e-mail: lauvil@uiuc.edu
fYear
2007
fDate
Oct. 30 2007-Nov. 1 2007
Firstpage
237
Lastpage
238
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
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Visual Analytics Science and Technology, 2007. VAST 2007. IEEE Symposium on
Conference_Location
Sacramento, CA, USA
Print_ISBN
978-1-4244-1659-2
Type
conf
DOI
10.1109/VAST.2007.4389035
Filename
4389035
Link To Document