We welcome contributions addressing all aspects of data mining, including but not limited to:

Methods and Algorithms

Anomaly & outlier detection
Big data & large-scale systems
Causal inference
Classification & semi-supervised learning
Clustering & unsupervised learning
Data cleaning & integration
Deep learning & representation learning
Feature extraction, selection and dimensionality reduction
Mining data streams
Mining graphs & complex data
Mining on emerging architectures & data clouds
Mining semi structured data
Mining spatial & temporal data
Mining text, web & social media 
Optimization methods 
Parallel and distributed methods
Pattern mining
Probabilistic & statistical methods

Applications of Data Mining

Business and marketing
Healthcare
Scientific data
Scientific data

Human Factors and Social Issues

Ethics of data mining
Intellectual ownership
Intellectual ownership
Privacy and fairness models 
Privacy preserving data mining
Risk analysis and risk management
Transparency and algorithmic bias
User interfaces and visual analytics