DIMACS Workshop on Streaming Data Analysis and Mining

November 5, 2001
DIMACS Center, CoRE Building, Rutgers University, Piscataway, NJ

Organizers:
Adam Buchsbaum, AT&T Labs - Research, alb@research.att.com
Rajeev Motwani, Stanford University, rajeev@cs.stanford.edu
Jennifer Rexford, AT&T Labs, jrex@research.att.com
Presented under the auspices of the Special Focus on Data Analysis and Mining.

Working Group on Streaming Data Analysis and Mining Home Page.


This material is based upon work supported by the National Science Foundation under Grant No. 0100921



The DIMACS Working Group on Streaming Data Analysis will begin with a public workshop on the topic, to be held on November 5, 2001, at DIMACS. At the workshop, participants in the working group will present current work on analyzing data streams.

Data stream analysis presents many practical and theoretical challenges. Many critical applications require immediate (seconds) decision making based on current information: e.g., intrusion detection and fault monitoring. Data must be analyzed as it arrives, not off-line after being stored in a central database. Processing and integrating the massive amounts of data generated by a number of continuously operating, heterogeneous sources poses is not straightforward. At some point, data sets become so large as to preclude most computations that require more than one scan of the data, as they stream by. Analysis of data streams also engenders new problems in data visualization. How is time-critical information best displayed? Can automatic response systems be created to deal with common cases? Etc.

Speakers at the workshop will discuss current work in all aspects of data stream analysis: theoretical issues, including modeling; practical issues, including work on existing systems; and bridges and bottlenecks, both current and potential, between theory and practice. The goal of the workshop and the ensuing working group is to foster interdisciplinary collaborations among researchers studying data streams from many disparate perspectives and application areas.


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Document last modified on May 16, 2001.