From Computer Data to Human Knowledge: A Cognitive Approach to Knowlege Discovery and Data Mining
Prgm Manager: Ephraim P. Glinert
IIS DIV OF INFORMATION & INTELLIGENT SYSTEMS
CSE DIRECT FOR COMPUTER & INFO SCIE & ENGINR
Start Date October 1, 1998
Expires September 30, 2001 (Estimated)
Investigator Michael J. Pazzani pazzani@ics.uci.edu
CO-PI: Dorrit Billman Georgia Tech School of Psychology
NSF Program 6856 KNOWLEDGE & COGNITIVE SYSTEMS
Abstract
The research is concerned with intelligent decision aids that can be
developed by data mining techniques. Experience has determined that
such systems can learn accurate models, but that experts in areas
where those models are used in decision aids are often reluctant to
trust them because they do not, for instance, use the same tests
intermediate conclusions or abstractions that the experts have grown
to trust. Or they do not use certain factors at all that experts feel
to be relevant. Experts also want models that are stable under small
changes in the data being analyzed. Psychologists have discovered
factors that simplify the learning, understanding, and communication
of category and process information by humans. This research seeks to
explore these psychological principles in light of the output of
existing KDD algorithms and then go on to develop and evaluate new KDD
algorithms that will provide output that is easy for people to learn ,
use, and communicate to others. With the results of this research, it
should be possible to make such decision aids more "human centered",
so that they will be used more often and more effectively in practice.
Michael J. Pazzani
Department of Information and Computer Science,
University of California, Irvine
Irvine, CA 92697-3425
pazzani@ics.uci.edu