DocumentCode :
1551740
Title :
Discovery visualization using fast clustering
Author :
Ribarsky, William ; Katz, Jochen ; Jiang, Frank ; Holland, Aubrey
Author_Institution :
Coll. of Comput., Georgia Inst. of Technol., Atlanta, GA, USA
Volume :
19
Issue :
5
fYear :
1999
Firstpage :
32
Lastpage :
39
Abstract :
To attack the problem of handling increasingly vast stores of information, we discuss a new approach to data exploration that requires the close coupling of man and machine. We call this approach discovery visualization to emphasize the importance of visual display and interaction. This approach aims to discover new relations, new features, and new knowledge. A key element in discovery visualization lies in heightening the machine´s awareness of users so they have, for example, focus-based manipulation, based on where and how closely they look at the displayed scene, in addition to direct manipulation. This process makes no sense unless the machine can respond immediately. Further, we promote the concept of continuous interaction with constant feedback between man and machine, and constant unfolding of the data. Finally, automated response must combine with user selection to achieve and sustain animated action, even in data sets of great or varying complexity
Keywords :
data mining; data visualisation; very large databases; automated response; continuous interaction; data exploration; data mining; data sets; direct manipulation; discovery visualization; fast clustering; focus-based manipulation; very large database; visual display; Animation; Clustering algorithms; Data visualization; Displays; Feature extraction; NP-complete problem; Neural networks; Shape; Silver; Simulated annealing;
fLanguage :
English
Journal_Title :
Computer Graphics and Applications, IEEE
Publisher :
ieee
ISSN :
0272-1716
Type :
jour
DOI :
10.1109/38.788796
Filename :
788796
Link To Document :
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