Advances in the Dempster-Shafer theory of evidence
A new version of the rule induction system LERS
Fundamenta Informaticae
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
A Logic Programming Framework for Rough Sets
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
A view on rough set concept approximations
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Hierarchical Classifiers for Complex Spatio-temporal Concepts
Transactions on Rough Sets IX
Feature selection for aiding glass forensic evidence analysis
Intelligent Data Analysis
Modeling complex architectures based on granular computing on ontology
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Approximation of sets based on partial covering
Theoretical Computer Science
Modeling rough granular computing based on approximation spaces
Information Sciences: an International Journal
Knowledge discovery by relation approximation: a rough set approach
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
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The concept of approximation is one of the most fundamental in rough set theory. In this work we examine this basic notion as well as its extensions and modifications. The goal is to construct a parameterized approximation mechanism making it possible to develop multi-stage multi-level concept hierarchies that are capable of maintaining acceptable level of imprecision from input to output.