9714104 Grossman This award supports a four-day workshop entitled "Mathematical Techniques to Mine Massive Data Sets". The goal of the workshop is to introduce a group of mathematical scientists to techniques used for the mining of massive data sets. Data mining is the automatic extraction and discovery of patterns, associations, changes, anomalies, and significant structures in large data sets. Large data sets generated by scientific, engineering, medical and business applications are becoming increasingly common. Developing algorithms which can uncover patterns in large data sets is an important mathematical challenge. In the past decade, extremely large sets of data have been generated at an alarming from very diverse areas including scientific, medical, communications, and manufacturing. These data bases are growing much faster than the speed of computers and thus are outstripping our ability to extract information with current techniques. The aim of this workshop is to acquaint mathematical scientists with the issues involved in the mining of massive data sets and to use their ability of abstraction to obtain new approaches to this critical problem.

Agency
National Science Foundation (NSF)
Institute
Division of Mathematical Sciences (DMS)
Type
Standard Grant (Standard)
Application #
9714104
Program Officer
Ann K. Boyle
Project Start
Project End
Budget Start
1997-06-01
Budget End
1997-11-30
Support Year
Fiscal Year
1997
Total Cost
$60,000
Indirect Cost
Name
University of Illinois at Chicago
Department
Type
DUNS #
City
Chicago
State
IL
Country
United States
Zip Code
60612