Rough Sets and Knowledge Technology 9th International Conference, RSKT 2014, Shanghai, China, October 24-26, 2014, Proceedings /

Rough Sets and Knowledge Technology 9th International Conference, RSKT 2014, Shanghai, China, October 24-26, 2014, Proceedings / [electronic resource] : edited by Duoqian Miao, Witold Pedrycz, Dominik Ślȩzak, Georg Peters, Qinghua Hu, Ruizhi Wang. - 1st ed. 2014. - XXVIII, 867 p. 178 illus. online resource. - Lecture Notes in Artificial Intelligence, 8818 2945-9141 ; . - Lecture Notes in Artificial Intelligence, 8818 .

Foundations and Generalizations of Rough Sets -- Attribute Reduction and Feature Selection -- Applications of Rough Sets -- Intelligent Systems and Applications -- Knowledge Technology -- Domain-Oriented Data-Driven Data Mining -- Uncertainty in Granular Computing -- Advances in Granular Computing -- Big Data to Wise Decisions -- Rough Set Theory -- Three-Way Decisions, Uncertainty, and Granular Computing.

This book constitutes the thoroughly refereed conference proceedings of the 9th International Conference on Rough Sets and Knowledge Technology, RSKT 2014, held in Shanghai, China, in October 2014. The 70 papers presented were carefully reviewed and selected from 162 submissions. The papers in this volume cover topics such as foundations and generalizations of rough sets, attribute reduction and feature selection, applications of rough sets, intelligent systems and applications, knowledge technology, domain-oriented data-driven data mining, uncertainty in granular computing, advances in granular computing, big data to wise decisions, rough set theory, and three-way decisions, uncertainty, and granular computing.

9783319117409

10.1007/978-3-319-11740-9 doi


Artificial intelligence.
Application software.
Database management.
Numerical analysis.
Data mining.
Pattern recognition systems.
Artificial Intelligence.
Computer and Information Systems Applications.
Database Management.
Numerical Analysis.
Data Mining and Knowledge Discovery.
Automated Pattern Recognition.

Q334-342 TA347.A78

006.3
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