题目：Mining Data Streams 报告人：Philip Yu, Professor and Wexler Chair
Department of Computer Science, University of Illinois at Chicago
ACM Fellow, IEEE Fellow 时间：7月25日（星期五）, 10:00-11:00
地点：蒙民伟楼404会议室 摘要：
The problem of streaming data has become increasingly importance in recent yea
rs. The ubiquitous presence of data streams in a number of practical domains h
as generated a lot of research in this area. Example applications include surv
eillance for terrorist attack, network monitoring for intrusion detection, and
others. Problems such as data mining which have been widely studied for tradi
tional data sets cannot be easily solved for the data stream domain. This is b
ecause the large volume of data arriving in a stream renders most algorithms t
o inefficient as most mining algorithms require multiple scans of data which i
s unrealistic for streaming data. More importantly, the characteristics of the
data stream can change over time and the evolving pattern needs to be capture
d. In addition, we need to consider the problem of resource allocation in mini
ng data streams. Due to the large volume and the high speed of streaming data,
mining algorithms must cope with the effects of system overload. Furthermore,
the stream data can often be noisy as in sensor data streams. Thus, how to ac
hieve optimum results under the various constraints becomes a challenging task
. In this talk, I’ll provide an overview, discuss the issues and focus on ho
w to mine uncertain data streams and perform resource adaptive computation.
简历：
Philip S. Yu received the M.S. and Ph.D. degrees in E.E. from Stanford Univers
ity, and the M.B.A. degree from New York University. He is a Professor in the
Department of Computer Science at the University of Illinois at Chicago and al
so holds the Wexler Chair in Information and Technology. He was manager of t
he Software Tools and Techniques group at the IBM Thomas J. Watson Research Ce
nter. His research interests include data mining, Internet applications and te
chnologies, database systems, multimedia systems, parallel and distributed pro
cessing, and performance modeling. Dr. Yu has published more than 500 papers i
n refereed journals and conferences. He holds or has applied for more than 300
US patents. Dr. Yu is a Fellow of the ACM and a Fellow of the IEEE. He is as
sociate editors of ACM Transactions on the Internet Technology and ACM Transac
tions on Knowledge Discovery from Data. He is on the steering committee of IE
EE Conference on Data Mining and was a member of the IEEE Data Engineering ste
ering committee. He was the Editor-in-Chief of IEEE Transactions on Knowledge
and Data Engineering (2001-2004). He has received several IBM honors includi
ng 2 IBM Outstanding Innovation Awards, an Outstanding Technical Achievement A
ward, 2 Research Division Awards and the 94th plateau of Invention Achievement
Awards. He was an IBM Master Inventor. Dr. Yu received a Research Contribut
ions Award from IEEE Intl. Conference on Data Mining in 2003 and also an IEEE
Region 1 Award for "promoting and perpetuating numerous new electrical enginee
ring concepts" in 1999. |
