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.