GVU Technical Report Number:
GIT-GVU-99-14
Title:
Discovery Visualization and Visual Data Mining
Authors:
William Ribarsky
Jochen Katz
Frank Jiang
Aubrey Holland
Abstract:
This paper describes discovery visualization, a new visual data mining
approach that has as a key element the heightened awareness of the
user by the machine. Discovery visualization promotes the concept of
continuous interaction with constant feedback between man and machine
and constant unfolding of the data. It does this by providing a
combination of automated response and user selection to achieve and
sustain animated action while the user explores time-dependent data.
The process begins by automatically generating an overview using a
fast clustering approach, where the clusters are then followed as
time-dependent features. Discovery visualization is applied to both
test data and real application data. The results show that the method
is accurate and scalable, and it offers a straightforward, error-based
process for improvement of accuracy.
Keywords:
Discovery visualization, data mining
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