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2017 IEEE Symposium on Computational Intelligence and Data Mining (IEEE CIDM' 17)

IEEE CIDM 2017 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 2017). IEEE CIDM 2017 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

Accepted Special Sessions

(To be announced)

Symposium Co-Chairs



Robi Polikar
Rowan University, Glassboro, NJ 08028, USA
Email: polikar@rowan.edu


Friedhelm Schwenker
Ulm University, Germany
Email: friedhelm.schwenker@uni-ulm.de


Barbara Hammer
Bielefeld University, Germany
Email: bhammer@techfak.uni-bielefeld.de


Gang Li
Daekin University, Melbourne, Australia
Email: gangli@gmail.com

Program Committee

(To be announced)