Call for Papers

The scope of the special session includes but is not limited to the following:

  • Temporal data clustering
  • Classification and regression of univariate and multivariate time series
  • Early classification of temporal data
  • Deep learning for temporal data
  • Learning representation for temporal data
  • Metric and kernel learning for temporal data
  • Modeling temporal dependencies
  • Time series forecasting
  • Time series annotation, segmentation, and anomaly detection
  • Spatial-temporal statistical analysis
  • Functional data analysis methods
  • Data streams
  • Interpretable/explainable time-series analysis methods
  • Dimensionality reduction, sparsity, algorithmic complexity, and big data challenges
  • Benchmarking and assessment methods for temporal data
  • Applications, including transport, urban computing, weather and climate, ecology, bio-informatics, medical, and energy consumption on temporal data

Proceedings, Indexing and Special Issues

All accepted full-length special session papers will be published by IEEE in the DSAA main conference proceedings under its Special Session scheme. All papers will be submitted for inclusion in the IEEEXplore Digital Library.

High-quality accepted papers will be recommended to a Special Issue of the¬†International Journal of Data Science and Analytics on “Learning from temporal data” through a fast-track process.