IEEE CIDM 2023 organized by the IEEE Computational Intelligence Society Data Mining Technical Committee is one of the largest and best attended symposia of the of the IEEE Symposium Series of Computational Intelligence (IEEE SSCI 2023). IEEE CIDM 2023 will bring together researchers and practitioners from around the world to discuss the latest advances in the field of computational intelligence applied to data mining and will act as a major forum for the presentation of recent results in theory, algorithms, systems and applications.
Topics
Topics related to all aspects of data mining and machine learning, such as theories, algorithms, systems and applications, particularly those based on computational intelligence technologies, are welcome; these include, but are not limited to:
- Neural networks for data mining
- Evolutionary algorithms for data mining
- Fuzzy sets for data mining
- Data mining with soft computing
- Foundations of data mining
- Mining with big data
- Classification, Clustering, Regression
- Association
- Feature learning and feature engineering
- Machine learning algorithms
- Mining from streaming data
- Deep learning
- Data mining from nonstationary and drifting environments
- Multimedia data mining
- Text mining
- Link and graph mining
- Social media mining
- Collaborative filtering
- Crowd sourcing
- Personalization
- Security, privacy and social impact of data mining
- Data mining applications
Symposium Chairs
- Zhen Ni
zhenni@fau.edu
Florida Atlantic University
Programme Committee
- Tufan Kumbasar, Istanbul Technical University
- Wil van der Aalst, Eindhoven University of Technology
- Sansanee Auephanwiriyakul, Chiang Mai University
- Ahmad Taher Azar, Benha University
- Giacomo Boracchi, Politecnico di Milano
- Qi Chen, Victoria University of Wellington
- Keeley Crockett, Manchester Metropolitan University
- Weiping Ding, Nantong University
- Gregory Ditzler, The University of Arizona
- Haibo He, University of Rhode Island
- Bach Nguyen Hoai, Victoria University of Wellington
- Ting Hu, Queen’s University
- Yonghong (Catherine) Huang, McAfee AI Research
- Ata Kaban, University of Birmingham
- Gang Li, Deakin University
- Yun Li, i4AI Ltd
- Jane Jing Liang, Zhengzhou University
- Simone Ludwig, North Dakota State University
- Paulo Lisboa, Liverpool John Moores University
- Patricia Melin, Tijuana Institute of Technology
- Sanaz Mostaghim, Otto von Guericke University of Magdeburg
- Su Nguyen, Hoa Sen University
- Yonghong Peng, University of Sunderland
- Robi Polikar, Rowan University
- Kai Alex Qin, Swinburne University of Technology
- Marek Reformat, University of Alberta, Canada
- Manuel Roveri, Politecnico di Milano
- Antonio Tallon
- Alfredo Vellido, Universitat Politècnica de Catalunya (UPC BarcelonaTech)
- Handing Wang, Xidian University
- Lipo Wang, Nanyang Technological University
- Anna M. Wilbik, Eindhoven University of Technology
- Guandong Xu, University of Technology Sydney
- Gary G. Yen, Oklahoma State University
- Yang Yu, Nanjing University
- Zhiwen Yu, South China University of Technology
- Mengjie Zhang, Victoria University of Wellington
- Dongbin Zhao, Institute of Automation, Chinese Academy of Sciences