GFX Café Seminar Friday May 16, 2008
12noon, ECE118
Food will be served
TITLE:
A Conceptual Framework for Visual Data Mining, with
Continuous Semantic Zooming
by Shan Xia, Visualization Laboratory, UNM
ABSTRACT:
Large-scale data sets are typically complex, making the interesting or
novel information hidden within them hard to discover. Data mining
algorithms and information visualization methodologies can help people
explore these data sets by extracting knowledge and representing it
in "meaningful" ways. This talk will describe a conceptual framework to
help in the understanding of unified data mining and information
visualization systems. To explore this framework, we implement an
archetypical hierarchical prototype that exposes the internal parameters
of the framework allowing the quantitative evaluation of its usefulness.
A pilot study that uses an information visualization technique referred to
as continuous semantic zooming in the visualization portion of the
prototype is presented that begins to support its positive performance.
This project will conduct a new series of larger scale human subject
experiments to further analyze and empirically characterize the effects on
human performance by unified systems designed in this manner.
BIO:
Shan Xia is a PhD candidate in the Visualization Laboratory at the Center
for High Performance Computing of the University of New Mexico, with
research interests in information visualization and data mining. She has
a M.S. degree in Electrical Engineering from the University of New Mexico.
--
Pradeep Sen
Assistant Professor
Advanced Graphics Lab
Dept. of Electrical & Computer Engineering
University of New Mexico
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