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WORLDCOMP'07 Tutorial
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Data Mining in Time Series and Multimedia Databases.
Dr. Eamonn Keogh University of California - Riverside, California, USA Date: Wednesday - June 27, 2007 Time: 6:00 - 9:30 PM Location: TBA |
Time series and multimedia data are ubiquitous; large volumes of such data are routinely created in scientific, industrial, entertainment, medical and biological domains. Examples include gene expression data, electrocardiograms, electroencephalograms, gait analysis, stock market quotes, space telemetry, microarrays, CAT Scans etc. Because such data is intrinsically real valued, most of the work on data mining of text has little utility for such datasets.
A decade ago, a seminal paper by Faloutsos, Ranganathan, Manolopoulos appeared in SIGMOD. The paper, Fast Subsequence Matching in Time-Series Databases, has spawned at least a thousand references and extensions in the database/ data mining and information retrieval communities. This tutorial will summarize the decade of progress in multimedia/time series information retrieval since this influential paper appeared.
Intended Audience
- Data mining (and Information Retrieval/Database) researchers. Both researchers in general and those working on specific time series/multimedia database problems will find the tutorial informative. The tutorial ends with a discussion of the ?top ten? problems to work on in the area, graduate students looking for an interesting problem in a hot area will be well served.
- Data mining educators (and Information Retrieval/Database). Many professors who teach data mining/information retrieval/databases/machine learning courses use his slides. Such individuals will received his comprehensive (and modifiable) slides and observe his presentation of them. They will be able to base 10 to 20 hours of graduate instruction on the tutorial.
- Data mining (and Information Retrieval/Database) application developers. They will learn the latest techniques/representations for indexing and mining time series/ multimedia data and examples of how the techniques fit into real-life applications.
Biography of the Presenter
Dr. Keoghs research interests are in Data Mining, Machine Learning and Information Retrieval. He has published more than 80 papers in these areas.
Several of his papers have won ?best paper? awards. In addition he has won several teaching awards. He is the recipient of a 5-year NSF Career Award for ?Efficient Discovery of Previously Unknown Patterns and Relationships in Massive Time Series Databases? and a grant from Aerospace Corp to develop a time series visualization tool for monitoring space launch telemetry.
Dr Keogh has given well received tutorials on time series, machine learning and data mining all over the world, and his papers have been referenced well over a 2,000 times.
Please see www.cs.ucr.edu/~eamonn/tutorials.html for addition information about his tutorials.
Dr. Eamonn Keogh
Associate Professor
Computer Science & Engineering Department
University of California - Riverside
California, USA
eamonn@cs.ucr.edu
