Tutorials

Accepted Tutorials for SDM09

Tutorial 1: Exploring Interaction Networks for Services Industry [PDF, 10MB]
S. Kameshwaran, Indian School of Business, India; Sameep Mehta and Vinayaka Pandit, IBM India Research Lab, India

Tutorial 2: Data Mining with Graphs and Matrices [PDF, 7MB]
Fei Wang and Tao Li, Florida International University; Chris Ding, University of Texas at Arlington

Tutorial 3: Mining When Classes are Imbalanced, Rare Events Matter More, and Errors Have Costs Attached [PDF, 2MB]
Nitesh Chawla, University of Notre Dame

Tutorial 4: A Geometric Perspective on Dimensionality Reduction [PDF, 2MB]
Deng Cai and Jiawei Han, University of Illinois at Urbana-Champaign; Xiaofei He, Zhejiang University, China

Call for Tutorials

The SIAM Data Mining (SDM09) Organizing Committee invites proposals for tutorials to be held in conjunction with the conference. Tutorials are an effective way to educate and/or provide the necessary background to the intended audience enabling them to understand technical advances.

For SDM09, we are seeking proposals for tutorials on all topics related to data mining. A tutorial may be a theme-oriented comprehensive survey, discuss novel data mining techniques or may center around successful and timely application of data mining in important application areas (e.g. medicine, national security, scientific data analysis). For examples of typical SIAM tutorials, see the set of accepted tutorials at previous SIAM conference archive.siam.org/meetings/sdm08/tutorials.php.

Tutorials are open to all conference attendees without any extra fees. The typical tutorial will be 2 hrs long (longer tutorials will be considered). Previous SDM conferences attracted up to 100 attendees in a tutorial.

Proposals should be submitted electronically by October 3, 2008 to:

Bart Goethals

Professor
Advanced Database Research and Modelling
University of Antwerp, Belgium
[email protected]

in PDF format (for other formats please contact the tutorial chair first). Proposals should include the following:

Timeline

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