2015 SIAM International Conference on Data Mining


  • 30 April - 02 May 2015
  • Vancouver, Canada
  • Organiser: SIAM
  • Event Details

Data mining is the computational process for discovering valuable knowledge from data. It has enormous application in numerous fields, including science, engineering, healthcare, business, and medicine. Typical datasets in these fields are large, complex, and often noisy. Extracting knowledge from these datasets requires the use of sophisticated, high-performance, and principled analysis techniques and algorithms, which are based on sound theoretical and statistical foundations. These techniques in turn require implementations on high performance computational infrastructure that are carefully tuned for performance. Powerful visualization technologies along with effective user interfaces are also essential to make data mining tools appealing to researchers, analysts, and application developers from different disciplines.

The SDM 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 presentations and tutorials (included with conference registration). A set of focused workshops is 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.

Themes and Topics of Interest

Methods and Algorithms
• Clustering
•Frequent Pattern Mining
•Probabilistic & Statistical Methods
•Graphical Models
•Spatial & Temporal Mining
•Data Stream Mining
•Anomaly & Outlier Detection
•Feature Extraction, Selection and Dimension Reduction
•Mining with Constraints
•Data Cleaning & Preprocessing
•Computational Learning Theory
•Multi-Task Learning
•Online Algorithms
•Big Data, Scalable & High-Performance Computing Techniques
•Mining with Data Clouds
•Mining Graphs
•Mining Semi Structured Data
•Mining Complex Datasets
•Mining on Emerging Architectures
•Text & Web Mining
•Optimization Methods
•Other Novel Methods

•Astronomy & Astrophysics
•High Energy Physics
•Collaborative Filtering
•Climate/Ecological/Environmental Science
•Risk Management
•Supply Chain Management
•Customer Relationship Management
•Genomics & Bioinformatics
•Drug Discovery
•Healthcare Management
•Automation & Process Control
•Logistics Management
•Intrusion & Fraud detection
•Sensor Network Applications
•Social Network Analysis
•Intelligence Analysis
•Other Novel Applications & Case Studies

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

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