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 :
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