CIS Department Talk-November 5, 2008
The Department of Computer and Information Science & The Society of
Computer Science Present
|Speaker:||Dr. Gary Weiss, Fordham University, Department of Computer Science
|Topic:||An Introduction to Data Mining and Utility-Based Data Mining
|Date:||November 5, 2008, 2:30PM-4:00PM|
|Place:||Dealy Hall, Room 205, LL Room 802 |
In the first part of this talk I will provide a general introduction to the discipline of data mining. This relatively new field has shown explosive growth over the past decade and its methods and techniques are now widely accepted and utilized in many areas (e.g., business intelligence). I will discuss what data mining is, what disciplines it arose from, why it is needed, how it works, and how it has been used to solve real-world problems. I will briefly describe some of the main data mining tasks, such as prediction, clustering, and association rule mining and some of the most commonly used methods, including decision trees and neural networks. In the second part of the talk I will discuss some deficiencies with early work in the field and a response to these deficiencies. Early work in data mining did not address the complex circumstances and rich environment in which data mining occurs. Over time it became clear that the standard assumptions that were being made were unrealistic and that economic utility had to be considered during the data mining process. Utility-Based Data Mining, a term introduced by myself and two of my colleagues, addresses these utility concerns in the data mining process. In the second part of my talk I will provide a brief overview of Utility-Based Data Mining and discuss some of my research within this area.
Gary Weiss is an assistant professor in the Computer and Information Science Department at Fordham University. His current research interests include machine learning and data mining and the fundamental issues that arise when tackling complex, real-world problems. Over the past few years he has conducted research in Utility-Based Data Mining and has promoted advances in this area by organizing two workshops on the topic and by editing a special issue of the Data Mining and Knowledge Discovery journal on this topic. Prior to coming to Fordham, he worked at Bell Labs and AT&T Labs, spending his last five years in industry in applying data mining methods to business and marketing problems. He received his B.S. from Cornell University, his M.S. from Stanford University, and his Ph.D. from Rutgers University.
Light refreshments will be served. For more information, contact Ms. Danielle Aprea (718) 817-4480