Topics of Interest

• Data Mining Foundations
• Parallel and Distributed Data Mining Algorithms,
• Data Streams Mining, Graph Mining,
• Spatial Data Mining, Text Video,
• Multimedia Data Mining, Web Mining,
• Pre-processing Techniques, Visualization,
• Security and Information Hiding in Data Mining.

Data Mining Applications

• Databases, Bioinformatics,
• Biometrics,
• Image Analysis,
• Financial Modeling,
• Forecasting, Classification,
• Clustering,
• Social Networks,
• Educational Data Mining.

Knowledge Processing

• Data and Knowledge Representation,
• Knowledge Discovery Framework and Process,
• Including Pre- and Post-processing,
• Integration of Data Warehousing,
• OLAP and Data Mining,
• Integrating Constraints and Knowledge in the KDD Process ,
• Exploring Data Analysis, Inference of Causes,
• Prediction, Evaluating,
• Consolidating, and Explaining Discovered Knowledge,
• Statistical Techniques for Generation a Robust,
• Consistent Data Model,
• Interactive Data Exploration/visualization and Discovery,
• Languages and Interfaces for Data Mining,
• Mining Trends,
• Opportunities and Risks,
• Mining from Low-Quality Information Sources.