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SDM'09: THE NINTH SIAM INTERNATIONAL CONFERENCE ON DATA MINING

John Ascuaga's Nugget, Sparks (Reno-Sparks-Tahoe area), Nevada, USA
April 30 - May 2, 2009

URL: http://www.siam.org/meetings/sdm09

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Important Dates:

Abstract Due: October 3, 2008
Manuscript Due: October 10, 2008
Author Notification: December 15, 2008
Camera Ready: January 26, 2009

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Data mining is an important tool in science, engineering, industrial
processes, healthcare, business, and medicine. The datasets in these
fields are large, complex, and often noisy. Extracting knowledge requires
the use of sophisticated, high-performance and principled analysis
techniques and algorithms, based on sound theoretical and statistical
foundations. These techniques in turn require powerful visualization
technologies; implementations that must be carefully tuned for
performance; software systems that are usable by scientists, engineers,
and physicians as well as researchers; and infrastructures that support
them.

This conference provides a venue for researchers who are addressing these
problems to present their work in a peer-reviewed forum. It also provides
an ideal setting for graduate students and others new to the field to
learn about cutting-edge research by hearing outstanding invited speakers
and attending tutorials (included with conference registration). A set of
focused workshops are also held on the last day of the conference. The
proceedings of the conference are published in archival form, and are also
made available on the SIAM web site.

=================Topics of Interest==========================

Methods and Algorithms:
Classification
Clustering
Frequent Pattern Mining
Probabilistic and Statistical Methods
Spatial and Temporal Mining
Data Stream Mining
Abnormality and Outlier Detection
Feature Selection / Feature Extraction
Dimension Reduction
Data Reduction
Mining with Constraints
Data Cleaning and Noise Reduction
Computational Learning Theory
Multi-Task Learning
Adaptive Algorithms
Scalable and High-Performance Mining
Mining Graphs
Mining Semistructured Data
Mining Complex Datasets
Mining on Emerging Architectures
Text and Web Mining
Other Novel Methods

Applications:
Astronomy & Astrophysics
High Energy Physics
Collaborative Filtering
Earth Science
Risk Management
Supply Chain Management
Customer Relationship Management
Finance
Genomics and Bioinformatics
Drug Discovery
Healthcare Management
Automation & Process Control
Logistics Management
Intrusion and Fraud detection
Bio-surveillance
Sensor Network Applications
Social Network Analysis
Intelligence Analysis
Other Novel Applications and Case Studies

Human Factors and Social Issues:
Ethics of Data Mining
Intellectual Ownership
Privacy Models
Privacy Preserving Data Mining and Data Publishing
Risk Analysis
User Interfaces
Interestingness and Relevance
Data and Result Visualization

=====================Organizing Committee =====================

STEERING COMMITTEE CHAIR
Chandrika Kamath, Lawrence Livermore National Laboratory

GENERAL CHAIRS
Haesun Park, Georgia Institute of Technology
Srinivasan Parthasarathy, The Ohio State University

PROGRAM CHAIRS
Huan Liu, Arizona State University
Zoran Obradovic, Temple University

WORKSHOP CHAIRS
Ian Davidson, University of California, Davis
Carlotta Domeniconi, George Mason University

TUTORIAL CHAIR
Bart Goethals, University of Antwerp

PUBLICITY CHAIRS
Aristides Gionis, Yahoo! Research, Barcelona
Lim Ee Peng, Nanyang Technological University, Singapore
Wei Wang, University of North Carolina

SPONSORSHIP CHAIRS
Wei Fan, IBM T. J. Watson Research Center
Vasant Honavar, Iowa State University

PUBLICATIONS CHAIR
Pang-Ning Tan, Michigan State University