• 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