Tolerance approximation spaces
Fundamenta Informaticae - Special issue: rough sets
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Nearness of Objects: Extension of Approximation Space Model
Fundamenta Informaticae - Special Issue on Concurrency Specification and Programming (CS&P)
Approximation Spaces and Nearness Type Structures
Fundamenta Informaticae - Special Issue on Concurrency Specification and Programming (CS&P)
On Three Closely Related Rough Inclusion Functions
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Monadic Algebras: a Standpoint on Rough Sets
Fundamenta Informaticae - Advances in Rough Set Theory
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The present paper is concerned with rough set theory (RST) and a particular approach to human-like induction, namely similarity coverage model (SCM). It redefines basic concepts of RST --- such like e.g. a decision rule, accuracy and coverage of decision rules --- in the light of SCM and explains how RST may be viewed as a similarity-based model of human-like inductive reasoning. Furthermore, following the knowledge-based theory of induction, we enrich RST by the concept of an ontology and, in consequence, we present an RST-driven conceptualisation of SCM. The paper also discusses a topological representation of information systems in terms of non-Archimedean structures. It allows us to present an ontology-driven interpretation of finite non-Archimedean nearness spaces and, to some extent, to complete recent papers about RST and the topological concepts of nearness.