SPEAKER: |
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TITLE: |
"Introduction to data mining" |
DAY: |
Friday, November 26, 1999 |
TIME: |
2:30 p.m. |
PLACE: |
BSB-108 Please note change of day, time and room! |
In this talk we shall explore the emerging area of data mining (also called knowledge discovery in databases). Data mining is loosely defined as the (automatic) extraction of novel information from very large databases. Data mining has been applied in a wide variety of application areas including business (marketing, finance, etc.), medicine, science and government. This talk presents a broad overview of the goals of data mining and the typical techniques used to try to accomplish the goals. We also discuss some interesting challenges data mining presents to Statisticians.
Stefan Steiner is an Assistant Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. He obtained his Ph.D. in Management Science from McMaster University in 1994, and M.Sc. and B.Math. degrees from the University of British Columbia and the University of Waterloo, respectively. Stefan's research interests include industrial statistics and applications of statistics in operations research and management science. Stefan is also an active consultant who has worked with a wide variety of organizations including General Motors Canada, Nortel Networks, Wescast, Petro Canada, Atlantis Aerospace, Woodbridge Foam, Eaton Yale, Plexus, the US Army, the State of Utah and some municipal governments. The consulting projects involved statistical process control, quality improvement, data analysis and process re-engineering.
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The reference below, which Dr Steiner has suggested as useful background for his talk, has been placed on reserve at Thode Library (STATS 770: Statistics Seminar):
[1] Adriaans, P. and Zantinge D. (1996), DATA MINING, Addison Wesley.