Special Session on Intelligent Data Mining: Techniques and Applications
Overview
Rapid advancements in big data and artificial intelligence technologies have had a profound impact on all areas of human society including the economy, management, politics, science, and education. Big data analytics employs a variety of artificial intelligence techniques including machine learning, deep learning, computational optimization, evolutionary computation, and swarm intelligence.
The special session aims at presenting the latest developments of the artificial intelligent algorithms in data mining, discussing the future direction of developments, and exchanging novel ideas about how to overcome the challenges. It welcomes the original contributions that provide novel theories, frameworks and applications to algorithms.
Topics
Topics of interest include, but are not limited to:
- Optimization Algorithms
- Evolutionary Computation Algorithms, Swarm Intelligence Algorithms for big data
- Machine learning and statistical methods for big data
- Feature Selection, Feature Extraction
- Dimensionality Reduction
- Data Preprocessing, Regression, Clustering and Classification
- Future Directions and Challenges in Intelligent Data Mining
- Industrial Challenges in Intelligent Data Mining
- Big Data mining for modeling, visualization, personalization, and recommendation
Submission
Please follow the DMBD 2021 instruction for authors and submit your paper via the DMBD 2021 online submission system. Please specify that your paper is for the Special Session on Optimization algorithms and Machine Learning for Data Mining.
Organizers
Prof. Ben Niu, Shenzhen University, China
Dr. Hong Wang, Shenzhen University, China
