TOPICS

• Theoretic foundations
• Novel models and algorithms
• Association analysis
• Clustering
• Classification
• Statistical methods for data mining
• Data pre-processing
• Feature extraction and selection
• Post-processing including quality assessment and validation
• Mining heterogeneous/multi-source data
• Mining sequential data
• Mining spatial and temporal data
• Mining unstructured and semi-structured data
• Mining graph and network data
• Mining social networks
• Mining high dimensional data
• Mining uncertain data
• Mining imbalanced data
• Mining dynamic/streaming data
• Mining behavioral data
• Mining multimedia data
• Mining scientific data
• Privacy preserving data mining
• Anomaly detection
• Fraud and risk analysis
• Security and intrusion detection
• Visual data mining
• Interactive and online mining
• Ubiquitous knowledge discovery and agent-based data mining
• Integration of data warehousing, OLAP and data mining
• Parallel, distributed, and cloud-based high performance data miningmining
• Opinion mining and sentiment analysis
• Human, domain, organizational and social factors in data mining
• Applications to healthcare, bioinformatics, computational chemistry, finance, eco-informatics, marketing, gaming, etc