About the Conference

Description

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.

Funding Agency

SIAM and the Conference Organizing Committee wish to extend their thanks and appreciation to the U.S. National Science Foundation for its support of this conference. (NSF Funding applies 2006-2008).

Themes

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

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
Intelligence Analysis
Sensor Network Applications
Social Network Analysis
Application Case Studies
Other Novel Applications

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

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