Track-1: Advance Computational Intelligence Techniques & Their Applications:
Pattern Analysis and Mining, Graphical Models, Spatial &Temporal Mining, Abnormality & Outlier Detection, Selection and Dimension Reduction, Mining with Constraints, Data Cleaning & Preprocessing, Computational Learning Theory, Novel Data Mining Algorithms, Big Data, Mining with Data Clouds, Mining Semi Structured Data, Mining Complex Datasets, Mining on Emerging Architectures, Text & Web Mining, Optimization Methods, Time Series and Sequential Pattern Mining, Visual data mining, Statistical foundations for robust and scalable data mining, Distributed data mining, Mining multi-agent data, Association rules, Audio Mining, Case-based reasoning and learning, Inductive learning including decision tree and rule induction learning, Statistical learning, Bayesian Models and Methods.