ABSTRACT: Continuous queries are those that produce continuous results on data streams. Such queries are useful in many application domains, including Network Management and Intrusion Detection, Web Monitoring, Sensor Network applications, and various financial and business applications. In this talk, we will first briefly discuss some of these applications and general technical challenges in dealing with such queries. We will then focus on similarity-based queries on streaming time series. These queries are to flag, on the incoming streaming time series, the appearance of some given patterns. We consider two scenarios. The first is when the number of given patterns can fit in the main memory, and the second cannot. These scenarios call for different considerations and techniques. We also present some experimental results to show the effectiveness of our techniques.

SPEAKER:  X. Sean Wang is an associate professor of information and software engineering at George Mason University, Fairfax, Virginia. His research areas include database systems, database support for temporal data and time series data, data mining, temporal reasoning, and information security. Professor Wang received a PhD in computer science from the University of Southern California, Los Angeles, California. He is a recipient of the U.S. National Science Foundation Career and Research Initiation Awards, and has published over 70 scientific papers in the general field of database systems.

Refreshments will be served starting at 2:00 PM.