Title: Discovering Patterns in Streams and Graphs
Time: August 9-12, 2004
Location: Room E207, Physicum, University of Helsinki, Gustav Hällströminkatu 2
Schedule: Lectures 12-16.
Grading: Active participation to all events of the course is required. The course will contain either a project work or an exam.
How does the Internet look like? Which temperature is anomalous, in a stream of temperature measurements?
The course focuses exactly on these two topics: how to find patterns (a) in numerical streams and (b) in large graphs. Both topics are attracting increasing interest. The first, streams, because of abundance of sensors that can collect enormous amounts of data, that need to be examined for patterns, outliers, abnormalities. The second, graphs, because of multiple emerging applications (computer networks, internet/web, biological networks, social networks).
The course will first cover fundamental tools for analysis, including signal processing (DFT, wavelets); time-series forecasting; matrix algebra (singular value decomposition); fractals and power laws. Then we will conclude with application of these tools on real datasets, like internet graphs, traffic and temperature measurements.
BIOGRAPHICAL NOTE:
Christos Faloutsos is a Professor at Carnegie Mellon University. He has received the Presidential Young Investigator Award by the National Science Foundation (1989), four ``best paper'' awards, and several teaching awards. He is a member of the executive committee of SIGKDD; he has published over 120 refereed articles, one monograph, and holds four patents. His research interests include data mining for streams and networks, fractals, indexing methods for spatial and multimedia bases, and data base performance.
For the course participants only:
Some of the transparencies are available from link. The username and password can be found from the email you have received.