Rough Sets

Core Rough Set Models and Methods.- An Application of Bayesian Confirmation Theory for Three-Way Decision.- Concept Approximation Based on Rough Sets and Judgment.- Rough Sets and the Algebra of Conditional Logic.- Rough Sets Defined by Multiple Relations.- On the Roughly Continuous Real Functions.- On topologies defined by binary relations in rough sets.- Iterative Set Approximations Based on Tolerance Relation.- Approximation Based on Representatives.- Local search for attribute reduction.- Rough Matroids Based on Dual Approximation Operators.- Studies on Reducing the Necessary Data Size for Rule Induction from the Decision Table by STRIM.- Rough Approximations on Two Universes under a Mapping.- Rough Sets Based on Possible Indiscernibility Relations in Incomplete Information Tables with Continuous Values.- The Prototype View of Concepts.- A Three-Way Clustering Algorithm via Decomposing Similarity Matrices for Multi-View Data with Noise.- Related Methods and Hybridization.- A Scalable Approach to Fuzzy Rough Nearest Neighbour Classification with Ordered Weighted Averaging Operators.- Learning Multi-granular Features for Harvesting Knowledge from Free Text.- Building a Framework of Rough Inclusion Functions by Means of Computerized Proof Assistant.- Membrane Systems and Multiset Approximation: The Cases of Inner and Boundary Rule Application.- Soft Petri Net.- Approximations induced by tolerance relations.- Three-Way Classification: Ambiguity and Abstention in Machine Learning.- Concepts Approximation Through Dialogue With User.- A Dynamic Dominance-based Rough Set Approach for Processing Ordered Data.- CSLI: Cost-sensitive collaborative filtering with local information embedding.- Attribute reduction based on optimistic multi-granulation information Systems.- Constructing the Optimal Approximation Sets of Rough Sets in Multi-granularity Spaces.- Discovering Flow Graphs from Data Tables Using the Classification and Prediction Software System