Topics of interest include, but are not limited to:
Foundations, algorithms, models and theory of data mining, including big data mining.
Deep learning and statistical methods for data mining.
Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data.
Data mining systems and platforms, and their efficiency, scalability, security and privacy.
Data mining for modelling, visualization, personalization, and recommendation.
Data mining for cyber-physical systems and complex, time-evolving networks.
Applications of data mining in social sciences, physical sciences, engineering, life sciences, web, marketing, finance, precision medicine, health informatics, and other domains.