The objective of the conference is to investigate rough set theory as receiving increasing attention in varied hybrid approaches in different practical fields, with a special emphasis on fostering interaction between academia and industry. Topics may include but are not limited to:

Core Rough Set Models and Methods:

  • Covering/Neighborhood-Based Rough Set Models,
  • Decision-Theoretic Rough Set and Dominance-Based Rough Set Methods,
  • Rough-Bayesian Models, Rough Clustering, Rough Computing, Rough Mereology,
  • Rough-Set-Based Feature Selection,
  • Rule-Based Systems,
  • Game-Theoretic Rough Set Methods,
  • Variable Consistency / Precision Rough Sets.

Related Methods and Hybridization:

  • Artificial Intelligence, Machine Learning, Pattern Recognition, Decision Support Systems,
  • Fuzzy Sets and Near Sets, Uncertain and Approximate Reasoning,
  • Information Granulation, Computing With Words,
  • Formal Concept Analysis, Petri Nets,
  • Intelligent Agent Models,
  • Interactive Computing, Nature-Inspired Computation Models,
  • Natural Language Processing,
  • Big Data Processing.

Areas of Applications:

  • Medicine and Health, Bioinformatics, Business Intelligence, Telecommunications, Smart Cities,
  • Transportation, Astronomy and Atmospheric Sciences,
  • Semantic Web, Web Mining and Text Mining,
  • Financial Markets, Retail and E-Commerce,
  • Computer Vision and Image Processing,
  • Cybernetics and Robotics,
  • Knowledge Discovery, Knowledge Engineering and Representation, Risk Monitoring.