We invite submissions of research papers addressing all aspects of discovery science. We particularly welcome contributions that discuss the application of data analysis, data mining and other support techniques for scientific discovery including, but not limited to, biomedical, astronomical and other physics domains. Applications to massive, heterogeneous, continuous or imprecise data sets are of particular interests.
Possible topics include, but are not limited to:
-Knowledge discovery, machine learning and statistical methods
-Ubiquitous knowledge discovery
-Data streams, evolving data and models
-Change detection and model maintenance
-Active knowledge discovery
-Learning from text and web mining
-Information extraction from scientific literature
-Knowledge discovery from heterogeneous, unstructured and multimedia data
-Knowledge discovery in network and link data
-Knowledge discovery in social networks
-Data and knowledge visualization
-Spatial/temporal Data
-Mining graphs and structured data
-Planning to learn
-Knowledge transfer
-Computational creativity
-Human-machine interaction for knowledge discovery and management
-Biomedical knowledge discovery and analysis
-Machine learning for high-performance computing, grid and cloud computing
-Applications of the above techniques to natural or social sciences