22nd IEEE International Conference on Data Mining (ICDM)

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.
We particularly encourage submissions in emerging topics of high importance such as ethical data analytics, automated data analytics, data-driven reasoning, interpretable modeling, modeling with evolving environment, cyber-physical systems, multi-modality data mining, and heterogeneous data integration and mining.