********************************************************************


                                                     Seminar

             Department of Systems Engineering and Engineering Management
                                  The Chinese University of Hong Kong

------------------------------------------------------------------------------------------

 

 

 

Title

:

Mining Uncertain Data Streams

 

 

 

Speaker

:

Prof. Philip S. Yu

 

 

Professor and Wexler Chair in Information Technology

 

 

Department of Computer Science, University of Illinois at Chicago

 

 

 

Date

:

May 26th, 2008 (Monday)

 

 

 

Time

:

4:30 p.m. - 5:30 p.m.

 

 

 

Venue

:

Room 513

 

 

William M.W. Mong Engineering Building

 

 

(Engineering Building Complex Phase 2)

 

 

CUHK

 

 

 

------------------------------------------------------------------------------------------

Abstract:
 

The problem of streaming data has become increasingly importance in recent years. The ubiquitous presence of data streams in a number of practical domains has generated a lot of research in this area. Example applications include surveillance for terrorist attack, network monitoring for intrusion detection, and others. Problems such as data mining which have been widely studied for traditional data sets cannot be easily solved for the data stream domain. This is because the large volume of data arriving in a stream renders most algorithms to inefficient as most mining algorithms require multiple scans of data which is unrealistic for streaming data. More importantly, the characteristics of the data stream can change over time and the evolving pattern needs to be captured. In addition, we need to consider the problem of resource allocation in mining 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 achieve optimum results under the various constraints becomes a challenging task. In this talk, I’ll provide an overview, discuss the issues and focus on how to mine uncertain data streams and perform resource adaptive computation.


-------------------------------------------------------------------------------------------

Biography:
 

Philip S. Yu’s main research interests include data mining, privacy preserving publishing and mining, data streams, database systems, Internet applications and technologies, multimedia systems, parallel and distributed processing, and performance modeling. He is a Professor in the Department of Computer Science at the University of Illinois at Chicago and also holds the Wexler Chair in Information and Technology. He was manager of the Software Tools and Techniques group at the IBM Thomas J. Watson Research Center. Dr. Yu has published more than 500 papers in refereed journals and conferences. He holds or has applied for more than 300 US patents.

Dr. Yu is a Fellow of the ACM and of the IEEE. He is associate editors of ACM Transactions on the Internet Technology and ACM Transactions on Knowledge Discovery from Data. He is on the steering committee of IEEE Conference on Data Mining and was a member of the IEEE Data Engineering steering committee. He was the Editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (2001-2004), an editor, advisory board member and also a guest co-editor of the special issue on mining of databases. He had also served as an associate editor of Knowledge and Information Systems. In addition to serving as program committee member on various conferences, he was the program chair or co-chairs of the IEEE Workshop of Scalable Stream Processing Systems (SSPS’07), the IEEE Workshop on Mining Evolving and Streaming Data (2006), the 2006 joint conferences of the 8th IEEE Conference on E-Commerce Technology (CEC\' 06) and the 3rd IEEE Conference on Enterprise Computing, E-Commerce and E-Services (EEE\' 06), the 11th IEEE Intl. Conference on Data Engineering, the 6th Pacific Area Conference on Knowledge Discovery and Data Mining, the 9th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, the 2nd IEEE Intl. Workshop on Research Issues on Data Engineering: Transaction and Query Processing, the PAKDD Workshop on Knowledge Discovery from Advanced Databases, and the 2nd IEEE Intl. Workshop on Advanced Issues of E-Commerce and Web-based Information Systems. He served as the general chair or co-chairs of the 2006 ACM Conference on Information and Knowledge Management, the 14th IEEE Intl. Conference on Data Engineering, and the 2nd IEEE Intl. Conference on Data Mining. He had received several IBM honors including 2 IBM Outstanding Innovation Awards, an Outstanding Technical Achievement Award, 2 Research Division Awards and the 93rd plateau of Invention Achievement Awards. He was an IBM Master Inventor. Dr. Yu received a Research Contributions Award from IEEE Intl. Conference on Data Mining in 2003 and also an IEEE Region 1 Award for \"promoting and perpetuating numerous new electrical engineering concepts\" in 1999.

Dr. Yu received the B.S. Degree in E.E. from National Taiwan University, the M.S. and Ph.D. degrees in E.E. from Stanford University, and the M.B.A. degree from New York University.


************************* ALL ARE WELCOME ************************

 

 

 

Host

:

Prof. Yu Xu, Jeffrey

Tel

:

(852) 2609-8309

Email

:

yu@se.cuhk.edu.hk

 

 

 

Enquiries

:

Prof. Nan Chen or Prof. Sean X. Zhou

 

:

Department of Systems Engineering and Engineering Management

 

 

CUHK

Website

:

http://www.se.cuhk.edu.hk/~seg5810

Email

:

seg5810@se.cuhk.edu.hk

 

 

 

********************************************************************